Project Specific Grants / Reserved topic scholarships 2014 | Doctoral Program - Information Engineering and Computer Science

Project Specific Grants / Reserved topic scholarships 2014

Computer Science

Project Specific Grants - Department of Information Engineering and Computer Science

CSTV1 - Algorithms for Human Behavior Understanding (2 +1 extra grant)
The goal of project is to develop new models for behavior understanding. The application area covers visual surveillance, crowd behavior analysis, activity recognition, object detection and tracking, face/gesture recognition and human-robot interaction. The approach should be able to catch personal and social experiences and use these as the main instrument to bridge the semantic and the social gaps. Research in multimodal event detection in video addressing complex human behaviour should also be considered. The candidates should have a good mathematical background and previous experience with OpenCV and Matlab.
Contact: niculae.sebe [at]

CSTV2 - System, methods and platforms for mental and physical training of older adults at home (1)
The project aims at stimulating mental and physical training of older adults while facilitating social relationships. It want to enable older adults (mainly independently living older adults) to understand and follow a training program together with a (possibly remote) group of "friends". The devices through which the training plans are delivered are tablets and smart TVs. Various types of sensing and monitoring technologies will be adopted not only to assess adherence to the plan, but to collect a sufficient amount of information to create a virtual social gym where trainees can have the feeling of training together with others in order to mantain a strong motivational aspect for the participants. The interaction with such devices is designed in such a way to avoid to the possible extent the need for assistance so that the trainees do not feel frustrated or with an increased sense of dependency. The project is an use case of the overall national programme "Active Aging at Home" - Progetto MIUR CLUSTER Tav CTN01_00128_297061.
Contact: prof Maurizio Marchese - maurizio.marchese [at]

Project Specific Grants - FBK

CSTV3 - Automatic Speech Transcription (1)
FBK has been pursuing research in automatic speech recognition (ASR) for two decades with the goal to develop state-of-the-art technology for interactive- and found-speech recognition, and to address applications ranging from speech analytics over the phone line to transcription of speech as found in any audio/visual document. Languages on which we are working with include Italian, English, Spanish, German, Dutch, Arabic, Turkish, Russian, Portuguese and French. Although FBK is interested in applicants in all areas of automatic transcription technology, most relevant topics for this Call are in the areas of acoustic modeling for large vocabulary ASR (which includes, for example, neural networks in ASR, building ASR systems for under-resourced languages, speaker adaptive training, methods for fast and efficient adaptation to changing application domains, data selection methods for acoustic model training), speaker diarization and spoken language detection. The candidate will team up a world-class research effort developing new ASR technology and advancing beyond the state-of-the-art, taking advantage from the large experience gained by FBK during the last 20 years.
Further information:
Contact: giuliani [at]

CSTV4 - Building the Web of Data exploiting Natural Language Processing (1)
Web of Data is about making information available on the Web accessible to machines and hence transforming how information can be found and manipulated. Of all recent initiatives oriented to create the Web of data, Wikidata is the most relevant. According to the promoters "the project aims to build a free knowledge base about the world that can be read and edited by humans and machines alike." In this PhD the candidate is asked to investigate natural language processing and machine learning techniques that can be used to automatically contribute to Wikidata. Specifically, it will be investigated semi-supervised approaches that can bootstrap from the data already available in Wikidata and other resources such as DBpedia and Freebase. Furthermore, careful consideration will have to be given to develop approaches applicable to different languages. Finally, as Wikidata will be edited by both humans and machines, active learning could play a crucial role and open new research challenges due to the crowd-sourcing approach: will the automatic approach be able to interact with the other users during the discussion necessary to collect/approve/filter the data to publish?
Further information:
Contact: giuliano [at]

CSTV5 - Distributed wireless networking for smart spaces (1)
Smart spaces are characterized by a large, complex set of devices and people interacting to enhance the user experience in a well-defined space. The goal of this thesis is to study elements of reliable wireless communication of sensor networks that form one of the core elements of the smart space. The candidate will work as part of a multi-disciplinary team working to develop a novel architecture for smart spaces.
Contact: murphy [at]

CSTV6 - Formal Methods for Safety and Dependability Assessment (1)
The design of complex critical systems requires the ability to analyse the behaviour in presence of faults, and to produce artifacts such as Fault-Trees and FMEA tables. Traditional techniques, applied in various sectors such as railways, avionics and space, are mostly manual, and are thus error prone and very costly. Recently, the use of formal methods has been proposed for the automated analysis of safety and dependability. Scalability and usabilty, however, remailn important issue. The thesis concerns the investigation of novel techniques for safety and dependability, able to automatically construct artifacts closer to the ones required in practice, and to increase the scalability by means of compositional reasoning. The aim is to obtain a formal environment for safety and dependability able to deal efficiently with large system-level designs.
Further information:
Contact: cimatti [at]

CSTV7 - Human in the loop for advanced machine translation (1)
Nowadays, human translation and machine translation are no longer antithetical opposites. Rather, the two worlds are getting closer and started to complement each other. On one side, the evolution of translation industry is witnessing a clear trend towards the adoption of Machine Translation (MT) as a primary support to professional translators. On the other side, the variety of data that can be collected from human feedback provides to MT research an unprecedented wealth of knowledge about the dynamics (practical and cognitive) of the translation process. The future is a symbiotic scenario where humans are assisted by reliable MT technology that, at the same time, continuously evolves by learning from translators activity. This grant aims to transform this vision into reality. The candidate will team up a world-class research effort developing new MT technology capable to integrate information obtained unobtrusively from real professional translation workflows. Relevant topics include: i) the extraction and generalization of knowledge (e.g. translation and correction strategies) from different types of human feedback, ii) projecting the acquired knowledge onto the core MT components, iii) modeling cognitive aspects of the translation process, iv) evaluating the effect of machine translation on human translation.
Further information:
Contact: turchi [at] negri [at]

CSTV8 - Machine Learning for Neuroscience (1)
The PhD research program aims at carrying out research activity on machine learning methodologies for neuroscientific data analysis. The main goal is design and deploy machine learning algorithms for cognitive neuroscience investigations based on neuroimaging. The research effort focuses on three specific tasks: brain decoding, brain mapping and brain connectivity. The challenge is to design effective computational methods for multivariate pattern analysis. The PhD research program will take place at NILab, the Neuroinformatics Laboratory raised as a joint initiative of Fondazione Bruno Kessler and the Center for Mind/Brain Sciences of the University of Trento.
Further information:
Contact: avesani [at]

CSTV9 - Model-based design and verification for CyberPhysical Systems (1)
A cyber-physical system (CPS) is a system of collaborating computational elements controlling physical entities and connected to the internet. CPSs can be found in areas as diverse as aerospace, automotive, chemical processes, civil infrastructure, energy, healthcare, manufacturing, transportation, entertainment, and consumer appliances. CPSs are required to carry out critical functions, and must implement an ever increasing number of interactive functions. The development of predictable CPSs is a fundamental challenge, and requires the definition of formal techniques and tools able to analyze the behaviour of interacting discrete/continuous dynamics, and to support the analysis of the design space. The thesis will investigate the relation (and will bridge the gap) between currently available techniques for CPS modeling, and formal verification techniques for continuous/discrete systems.
Contact: cimatti [at]

CSTV10 - Reasoning-based Process Mining (1)
Process mining is a recent and rapidly emerging research field, aiming at discovering, monitoring and improving real processes by extracting knowledge from event logs readily available in today's (information) systems [1]. The growing diffusion of information systems able to trace, monitor and store process executions, indeed, has made more and more concrete the possibility to provide powerful process analyses, making thus possible to identify bottlenecks in the process execution or misalignments between executions and existing models, to offer aggregated and statistical analyses as well as to predict future problems and suggest model improvements (e.g., pruning no more executed flows). However, despite the several enormous steps carried on in the last decade, as witnessed by the Process Mining Manifesto [1], still a number of open challenges waits to be addressed in this field, as for example, the run-time operational support for processes (i.e., the on-line detection and prediction of problems, and the run-time provision of recommendations towards their resolution), or the management of complex event logs with different characteristics (e.g., too many, too few or too abstract data).
The aim of this thesis is investigating how to exploit, adapt and combine techniques and approaches borrowed from different research fields, ranging from logic to artificial intelligence, from model checking to statistics, to advance the existing services for process analysis and process model (re-)design from monitoring data. The reasoning-based services provided as output can be for example the verification of complex requirements, constraining the control flow or other dimensions as time or data, or the definition and provision of new metrics and key performance indicators (KPIs). To this purpose, several are the challenges to be faced in the work as, for example, (i) the capability to represent and reason about secondary aspects for business processes such as data, time, resources; (ii) the capability to align execution information with models, when they exist, or to discover models from traces, when they do not exist; (iii) the capability to manage and reason on extremely large quantity of data (big data); (iv) the capability to realize the abovementioned analyses at run-time. The work will put together theoretical and methodological aspects, including for example the problem conceptualization and representation, as well as implementation and optimization ones, aimed at the development of process analysis services and tools.
[1] Wil M. P. van der Aalst et al., Process Mining Manifesto. Business Process Management Workshops (1) 2011: 169-194
Contact: ghidini [at]

CSTV11 - Security testing of smartphone applications (1)
In order to win the race against competitors, mobile applications for tablets and smart-phones are often developed with fast time-to-market approach. For this reason, development effort is often committed to deliver novel and engaging features and less attention is devoted in reviewing the quality of the code. As a result applications are released that still contain defects, faults and potential security problem. Novel approaches need to be elaborated to automate the testing phase of mobile applications, with a particular attention to security aspects, as a fundamental support to ensure both high quality and fast development model. This includes the elaboration of novel techniques for identification of potential security defects, for automatic test case generation and for developing an oracle to assess whether the system under analysis passes all the brand new test cases.
Further information:
Contact: ceccato [at]

CSTV12 - Software development for emerging markets (1)
Emerging software development methodologies, such as participated design (e.g., Living Labs), component-based software development (e.g., RubOnRails), and agile development (e.g., SCRUM), allow teams to build solutions which are fit to the needs of users, while reducing time to market and overall production costs. This is particularly important emerging and mature economies alike, since user-adoption and time-to-market are two main goals, which can make the difference between failure and success. The trade-off is that the code tends to grow disorderly and without a reference architecture. The issue is particularly evident with web applications, which are so often based on one or more (scripting) language to manage the business logic (e.g., Ruby, PHP, Python, Java) and Javascript for the front-end interaction. As interaction with users and agile sprints help the team deliver value to the customer, the code base tends to grow disorderly, data structures are replicated in different layers, and maintenance can become a serious issue. The grant has the goal of investigating and improving current practices and tools to build software products for emerging markets, while taking into account other non-functional constraints, such as maintainability.
Further information:
Contact: adolfo.villafiorita [at]


Extra grants - project-specific grant made available AFTER the publication of this Call

If you are interested in a applying for a project-specific grant made available AFTER the publication of this Call you must fill in the field "Other" of the Application online with the exact code/s and title/s of the project-specific grant

Project Specific Grants - FBK

CSTV13 - Modeling Human Social Dynamics (1)
Human behaviors, habits and emotions are strongly influenced by social contacts. Recent studies claimed that obesity, smoking, emotions and other behaviors and states are contagious. More in general, the social diffusion phenomena, in which a behavior spreads over a social network, are explained by a mechanism of behavioral cascading whereby the probability for a group member to adopt a behavior is affected by the adoption behavior of the other group members. In many aspects, this approach is similar to a popular model of spreading epidemics. However, there have recently been also some concerns about whether survey data were sufficient to properly establish this contagiousness, and whether the claimed contagion could be otherwise explained by people with similar behaviors preferring to spend time together (e.g. homophily). Closely tracking the locations and proximities of people in communities over a span of months enables us to better determine the relationships between changing behavior and changing social network - whether strangers of the same "feather" are more likely to share time and space, and whether friends have increasingly-similar schedules. The causal relationship in dispute has practical implications: in fact, if individual behavior is contagious, then we can change this behavior either by changing the behavior of several influential elements in the social network, or by changing the social network itself. The goal of the PhD project is to study these issues in really challenging contexts such as working environments, schools and universities, and daily lives.
Contact: lepri [at]

CSTV16 -  Natural language processing and production of persuasive messages (1)
The thesis will be concerned with the development of a computational system for producing persuasive messages and forms of creative language, like novel metaphors and metonymies. Persuasion techniques considered will be along what Petty and Cacioppo termed the  peripheral route to persuasion, rather than based on argumentation. The technology will include rhetorical, affective,  semantic, phonetic aspects.
Personalisation and adaptation to the context will also be studied.
The computational aspect will be complemented with studies on the language of persuasion and experiments on the effectiveness of the message. So the result of the dissertation will be a model and a system for the production of persuasive and creative messages. Applications are for personalised promotion campaigns and advertisement, health and well being, education, messages in situation of crisis.
Contact: stock [at]

Project Specific Grants - Telecom Italia S.p.A.

CSTV14 - Heterogeneous Big Data profiling and quality increase (2)
Nowadays we see data in volumes varieties and velocities that we have never seen before. A fundamental requirement for every large scale data set is to get an accurate insight and generate a profile, i.e., a compact description of the fundamental properties of the data. Typical data profiling tools are simply using statistical methods or graphical models to communicate their results to the user. However, they rarely combine this with data quality in order to provide a holistic evaluation of the data set. Data quality has so far been considered a separate task.This call is for a thesis on data profiling and data quality. The PhD candidate will be asked to develop state of the art solutions, theories and implementations that will promote the existing state in the specific domain. It will enable other researchers and practitioners alike to gain better insight of Big Data and significantly improve the work of modern data scientists.
Contact: velgias [at]

CSTV15 - Data-driven modeling of society's health (1)
Nowadays, there are almost 5 billion of mobile phone users worldwide, with millions of new subscribers every day. More importantly, mobile phone data can be "reality mined" to understand the patterns of human behavior, monitor our environments, and plan interventions for improving quality of life and for the social development. We can, in fact, analyze the “digital breadcrumbs” people leave behind as they go about their daily lives to dynamically model aggregate human behavior. For example, GPS data collected from drivers’ cell phones in a city can provide minute-by-minute updates on traffic flow. Moreover, the proliferation of GPS-enabled devices makes it possible to directly measure human behavior. Where do people eat? Where do people work? Where do people hang out? In which ways do interactions among people affect economic productivity or public health? Such data may provide also useful epidemiological insights: e.g. how might an influenza, driven by physical proximity, spread through a population?
Hence, we can learn what a “macro” social network of society looks like and how it evolves over time. Phone companies have also records of all the call patterns among their customers over multiple years. These data can paint a comprehensive picture of societal-level communication patterns.
The goal of the PhD student will be building predictive models from different sources of data (Call Detail Records, geo-tracked behaviors, social media, government open data, public health data, etc.) able to capture the social well-being and the health of of a large area such as the greater metropolitan area of a city or of an entire country. The student will conduct his research also leveraging the international collaborations that FBK and Telecom Italia hold with top-level universities (MIT and Northeastern).
Contact: lepri [at]

Project Specific Grants - Trento RISE, Fondazione Bruno Kessler and OpenContent SCARL

CSTV17 - Large-Scale Global Optimization of Semantic Metadata (1)
Semantic technologies are becoming pervasive for a variety of applications,  and various semantic taggers (e.g. named entities recognition, semantic role labeling, word sense disambiguation, geo-tagging, linking to ontologies) are developed to assign metadata that enrich text repository. Such taggers, however, are usually considered as independent each other, resulting in a poor global consistency of the extracted metadata. For instance, it might be the case that a certain occurrence of “Giuseppe Verdi” is tagged as PERSON by a tagger and is then linked to a LOCATION concept by another tagger. In this Thesis we intend to investigate innovative techniques for optimizing metadada consistency applied to large-scale archives. To this purpose the Thesis will explore both automatic techniques (e.g. based on clustering) and semi-automatic methodologies (e.g. based on  Active Learning).
This PhD thesis will be carried on as a collaboration between FBK (Human Language Technology research unit) and Opencontent S.C.a.R.L.
Contact: magnini [at]

Project Specific Grants - Trento RISE, Fondazione Bruno Kessler and SpazioDati S.r.l.

CSTV18 - Infrastructures and workflows supporting higly explorative data management of structured and unstructured data (1)
The term “Knowledge Graph” has recently become popular thanks to Google, Facebook, Yahoo and Microsoft, who announced the transitioning from traditional “search & data management” strategies to Knowledge Graph based approaches, which combine “Semantic” technologies and “Big Data” methodologies. At the same time we experienced an increasing availability of public data (“Open Data”) provide by both Public Administrations and civil society.
The objective of the research is to improve the current state of the art of Knowledge Graph creation and administration methodologies, and to contribute in defining a next generation approach based on “exploration based data refinement” and on an agile pipeline for data integration. Approaches such as “DevOps” and “Semantic Big Data processing”, will be the foundational elements of a study that tends to develop new agile methodologies for analysis (including also machine learning techniques), administation and interactive exploration of highly dynamic, variable and heterogeneous data. The goal is to allow on-demand Knowledge Graphs creation, using data provided by Spaziodati and it’s partners, to be used in real business contexts (banking, finance, tourism, heathcare).
The candidate should possess solid bases of machine learning, Database theory, software engineering, software development, unix system administration and a strong attitude toward scientific research problem tackling.
Contact:  tummarello [at]

Project Specific Grants - Trento RISE, Department of Information Engineering and Computer Science and SpazioDati S.r.l

CSTV19 -Improving disambiguation in textual annotation with large-scale graph analysis (1)
 dataTXT is a fast and scalable automatic annotator which identifies relevant terms from short textual snippets, and annotates them with Wikipedia concepts. Its main goal is providing support for companies that need to extract meaningful content from public data, such as those present in mass social media services (e.g. Twitter).
Currently, however, its algorithms are highly coupled to the Wikipedia graph, and its feasibility on other data graphs (e.g. Freebase) is poorly understood. This position is about taking dataTXT to the next level, by providing a general approach and a theory for performing practical graph-based disambiguation. Challenges arise due to the complexity and massiveness of the datasets involved, and to the scalability requirements of the product, which has to remain fast despite the scale of the knowledge graph. The work will be performed with the joint scientific coordination of the Department of Information Engineering and Computer Science (DISI) of the University of Trento (under the supervision of Professors Alberto Montresor and Yannis Velegrakis), and SpazioDati srl. Results from this research will have immediate practical (and commercial) implications.
You can read more about this proposal here.

Project Specific Grants - Trento RISE, Department of Information Engineering and Computer Science and Centro Ricerche GPI s.r.l.

CSTV20 -Weak-processes modelling and management in socio-technical environments (1)
 The theme of this project is how to use methodologies coming from the social sciences for managing processes that cannot be successfully formalised using standard modelling tools. These kinds of processes are characterised by  weakly connected activities, with low correlations and low predictability, but where there are significant needs for some form of formalisation, for instance for traceability of the activities.
The processes must be seen as "mapping" of a complex socio-technical arrangement, where several actors interact in different modalities but with activities that must be coordinated, effective, and accountable. An example is the case of the complex arrangements between patient, doctors, nurses, relatives, formal and informal caregivers.
Modelling and managing such weak processes in socio-technical environments, will require to start with current social sciences methodologies for extending the current modelling tools and methodologies.
Contact: vincenzo.dandrea [at]

Project Specific Grants - Trento RISE, Fondazione Bruno Kessler and Centro Ricerche GPI s.r.l.

CSTV21 -Socio-technical and Gamified Systems for managing Health and Wellbeing (1)
According to the WHO (World Health Organization), various health risk factors are related to life-style and dietary habits and the number of pathologies due to bad dietary habits are growing both in developed and in developing countries.
The purpose of this scholarship is to develop innovative methods and techniques to enhance awareness about one's personal dietary habits and educating towards behaviors which are more adherent to national and international guidelines. More in details, we intend to experiment gamification techniques to build and experiment systems which allow to enable forms of quantified-self (systematic data gathering on life habits related to nutrition) and peer-pressure (pressure by peers to change behaviors). The goals of the scholarship include conceptual design, prototype implementation, and experimentations to verify the effectiveness of such systems, with the ultimate goal of understanding what techniques are more effective in inducing changes.
The activity is characterized by research in social innovation with a great potential industrial impact. We After a preliminary analysis to evaluate the state of the art, one or more prototypes will be developed to verify their impact and effectiveness. Data gathering (respecting personal privacy rights) will then allow the candidate to quantitatively evaluate the hypotheses initially formulated, and the selection of the most promising solutions. Activities will be planned following SCRUM monthly sprints to guarantee strategic guidance and the flexibility required by this kind of activity. The ideal candidate has a strong propension to innovation, excellent research and programming skills. The candidate will work in CRG (Centro Ricerche GPI,, and in the ICT4G group of FBK (,, in an international and innovative environment, providing access to excellent facilities and resources.
Contact: adolfo.villafiorita [at]

Project Specific Grants - Department of Information Engineering and Computer Science

CSTV22 -Ageing in place: a respectful approach (1)
Academic and industrial research on the elderly has grown rapidly. Different projects have been funded both at national and global level. Many of them analyse the “ageing in place”, the ability for people to stay in their homes as they get older. It is seen as a solution to the rapid growth of the elder population and is also the wish of many senior citizens who prefer to stay longer and more autonomous in their home. A rapidly growing body of research is investigating the role of assistive technologies for supporting ageing in place. Various of such studies have demonstrated the appropriateness of using ethnography as a research method. However a careful study on the contribute of ethnography for researching ageing looking both at social and technological aspects lacks. This project has the goal of assessing the role of such methodology with a socio/technical perspective, aimed at defining an approach on the one hand respectful of the elders and on the other hand providing significant inputs for developing and implementing assistive technologie
Contact: vincenzo.dandrea [at]

CSTV23 -Building Playful Interaction (1)
This project revolves around the development of new interactive toys for children learning during their early childhood. The successful candidate will develop and evaluate tangible artifacts to engage young children. The ideal candidate has a strong background in Computer Science (a degree in Computer Science is a plus). He or she has expertise in hardware of software development and in Human-Computer Interaction.
Contact: antonella.deangeli [at]

CSTV24 -Designing Playful Interaction (1)
This project will explore new interactive strategies for children learning during their early childhood. The successful candidate will design tangible artifacts to engage young children. The ideal candidate has a strong background in Product Design. He or she has expertise in Interaction Design and in Human-Computer Interaction.
Contact: antonella.deangeli [at]




Project Specific Grants - Department of Information Engineering and Computer Science

TLCTV1 - Development of advanced signal and data processing methods for the analysis of data acquired by planetary radar sounders (1 + 1 extra-grant*)
The activity will be carried out in the framework of the "Radar for Icy Moon Exploration (RIME)" instrument on board of European Space Agency "JUpiter ICy moon Explorer (JUICE)". RIME is a low frequency radar sounder (i.e. a ground penetrating radar operated from a satellite platform) designed to investigate the Jupiter Icy Moons (i.e. Ganymede, Europa, and Callisto). The activity will be related to the simulation of the performance of the radar sounder and to the definition of automatic techniques for the analysis of the radargrams acquired by the sounder for the definition of the ground segment processing chain. The research will be carried out at the Remote Sensing Laboratory (RSLab) in the Department of Information Engineering and Computer Science of the University of Trento (see
Contact: bruzzone [at]

* The extra-grant is founded by Department of Information Engineering and Computer Science and Thales Alenia Space Italy

TLCTV2 - Development of advanced techniques for the automatic anlysis of optical and SAR satellite remote sensing images of Earh Observation (1)
This PhD Position requires specific know-how and basic knowledge in the field of optical remote sensing (i.e. multispectral and hyperspectral images) and/or active remote sensing (i.e. Synthetic Aperture Radar and/or LiDAR data). The research activity will be focused on the development of automatic techniques for data analysis (including automatic classification, change detection and data fusion). The activity will consider satellite and UAV images. The research will be carried out at the Remote Sensing Laboratory (RSLab) in the Department of Information Engineering and Computer Science of the University of Trento (see
Contact: bruzzone [at]

TLCTV3 - Protocol and Architectures for a Sustainable Internet (1)
The PhD position will be aimed at studying solution for developing an energy-efficient Internet, focusing on protocol performance in heterogenous scenarios (as expected by 5G technology) and on service delivery architectures. Specific attention will be paid on analyzing the environmental footprint of the Internet
Contact: fabrizio.granelli [at]

Project Specific Grants - FBK

TLCTV4 - Remote sensing for environmental monitoring (1)
Remote sensing demonstrated to be one of the most effective technologies for environmental monitoring and natural resources control. Examples of challenging scenarios addressed by using remote sensing are: agriculture, forestry, cadastre, urban planning, civil protection, geology, glaciology and nivology, surveillance, climate change. Within each single scenario several specific applications can be identified that requires specific solutions. Developing such kind of solutions requires the deep understating of applications and user needs, the development of customized systems, and often the integration of remote sensing technology with other technologies like the one related to proximal sensing.
Contact: bovolo [at]

TLCTV5 - Remote sensing image processing (1)
The remote sensing community can access to a huge number of images acquired in the last 30 years by several satellite-borne sensors showing different properties in terms of spatial, spectral and temporal resolution. With the new generations of sensors the amount of data and their diversity is continuously increasing. Accordingly there is an increment in the possible usage of remote sensing data. New applications arise that that requires the development of novel methodologies in the field of pattern recognition, image processing and data fusion for an effective information extraction from the data. In greater detail there is a need to develop methodologies able to effectively model: i) very high geometrical resolution images; ii) very high spectral resolution images ; iii) time series time series of images, etc.
Contact: bovolo [at]