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International KES Conference on Human Centred Intelligent Systems, KES-HCIS 2020

作者： Mbarki, Amal Naouai, Mohamed Faculty of Sciences of Tunis University of Tunis EL MANAR B.P. No. 94 - Rommana Tunis1068 Tunisia Computer Science Laboratory in Algorithmic and Heuristic Programming University Campus Farhat Hached Tunis Tunisia

ISBN: (纸本)9789811557835

The capacity to recognize perceptual organizations is a conventional human ability that demonstrates a peerless challenge for researchers of computer science. Compared to object recognition and image segmentation, which are considered as the primary interests of the image processing research, visual perception has fewer generic solutions or evaluated approaches. In this paper, we explain the difficulty of the visual perception process and we offer a structured survey of the related approaches. We focus on each approach, along with its advantages and disadvantages. Then we present a comparison and an evaluation of different approaches based on a number of chosen criteria. Finally, we propose an approach to model the visual perception using stochastic geometry. To solve the problem of pixel-based approach and to inject high-level knowledge, we propose a marked point process model. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2020.

关键词： Surveys

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New taxonomy of classification methods based on Formal Concepts Analysis 5

New taxonomy of classification methods based on Formal Conce...

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5th International Workshop "What can FCA do for Artificial Intelligence"?, FCA4AI 2016

作者： Trabelsi, Marwa Meddouri, Nida Maddouri, Mondher Laboratory of Computing Programming Algorithmic and Heuristic - LIPAH Faculty of Science of Tunis - FST El Manar University Tunis Tunisia Management College Jeddah University Saudi Arabia

Data mining is an essential step in knowledge extraction from data. Various approaches have been proposed in supervised classification of data, among them approaches based on Formal Concept Analysis. In this paper we present a new taxonomy of classification methods based on Formal Concept Analysis. © 2016, CEUR-WS. All rights reserved.

关键词： Formal concept analysis

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Approach of texture signature determination — Application to forest cover classification of high resolution satellite image

Approach of texture signature determination — Application t...

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International Conference of Soft Computing and Pattern Recognition (SOCPAR)

作者： Wala Zaaboub Zouhour Ben Dhiaf Faculty of Science of Tunis FST Laboratory of computer science programming algorithmic and heuristic Tunis Tunisia

This paper presents an approach of textural signature identification for the classification of high resolution satellite image of forest. We are looking for the most appropriate combination of features from texture measures. This combination which forms our signature should allow the discrimination between different types of textures present in the image that will be classified. We improve our signature by a step of weighting features. The weight of each feature reflects its degree of confidence. We finish with an experimental step which is an application of our combined weighted signature for the purposes of classification of high resolution satellite image of forest.

关键词： Feature extraction Satellites Fractals Satellite broadcasting Error analysis Histograms Synchronous digital hierarchy

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Generic discounting evaluation approach for urban image classification

Generic discounting evaluation approach for urban image clas...

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2013 International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making, IUKM 2013

作者： Samet, Ahmed Hammami, Imen Lefèvre, Eric Hamouda, Atef Laboratory of Research in Programming Algorithmic and Heuristic Faculty of Science of Tunis Tunisia Univ. Lille Nord de France UArtois EA 3926 LGI2A 62400 Báthune France

ISBN: (纸本)9783642395147

Belief function theory provides a robust framework for uncertain information modeling. It also offers several fusion tools in order to profit from multi-source context. Nevertheless, fusion is a sensible task where conflictual information may appear especially when sources are unreliable. Therefore, measuring source's reliability has been the center of many research and development. Existing solutions for source's reliability estimation are based on the assumption that distance is the only factor for conflictual situations. Indeed, integrating only distance measures to estimate source's reliability is not sufficient where source's confusion may be also considered as conflict origin. In this paper, we tackle reliability estimation and we introduce a new discounting operator that considers those two possible conflict origins. We propose an automatic method for discounting factor calculation. Those factors are integrated on belief classifier and tested on high-resolution image classification problem. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Uncertainty analysis

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An edge-region cooperative multi-agent approach for buildings extraction

An edge-region cooperative multi-agent approach for building...

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2012 2nd International Conference on Digital Information and Communication Technology and it's Applications, DICTAP 2012

作者： Sellaouti, Aymen Sghaier, Moslem Ouled Hamouda, Atef Laboratory of Computing in Programming Algorithmic and Heuristic Faculty of Sciences of Tunis Campus Universities Tunisia Tunisia Image Sciences Computer Sciences and Remote Sensing Laboratory University of Strasbourg France

ISBN: (纸本)9781467307338

This paper presents a new approach for automatic building detection in very high resolution satellite images. The proposed method is a cooperative multi-agent approach between both an edge and region approach. In the pretreatment step, a supervisor agent finds a building's corner using Harris detector. Starting from these points, a cooperation process is used to extract buildings. Experiments are done on images of Strasbourg city taken by Quickbird. © 2012 IEEE.

关键词： Buildings

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An edge-region cooperative multi-agent approach for buildings extraction

An edge-region cooperative multi-agent approach for building...

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International Conference on Digital Information and Communication Technology and it's Applications (DICTAP)

作者： Aymen Sellaouti Moslem Ouled Sghaier Atef Hamouda Laboratory of Computing in Programming Algorithmic and Heuristic Faculty of Sciences of Tunis Tunisia Image Sciences Computer Sciences and Remote Sensing Laboratory University of Strasbourg France Laboratory of Computing in Programming Algorithmic and Heuristic Faculty of Sciences of Tunis Faculty of Sciences of Tunis Tunisia Laboratory of Computing Programming Algorithmic and Heuristic Faculty of Sciences of Tunis Faculty of Sciences in of Tunis Tunisia

关键词： Buildings Image edge detection Detectors Image segmentation Vegetation mapping Educational institutions Radiometry

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Hierarchical classification-based radon road extraction (HCBRRE)

Hierarchical classification-based radon road extraction (HCB...

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International Conference on Control, Automation, Robotics and Vision (ICARCV)

作者： Aymen Sellaouti Hmida Rojbani Atef Hamouda Cedric Wemmert Aline Deruyver Laboratory of Computing in Programming Algorithmic and Heuristic Faculty of Sciences of Tunis Tunis Tunisia Image Sciences Computer Sciences and Remote Sensing Laboratory University of Strasbourg Strasbourg France

A hierarchical classification based road extraction approach is proposed in this paper. In order to extract road network, a spectral based-classification associates a confidence score to each region in the image. This score is used to extract road region and its constraints for each iteration of the hierarchy. Road localization is based on Radon transform and expert knowledge. The quality assessments in urban area images show the benefits of the introduced approach.

关键词： Roads Image segmentation Accuracy Feature extraction Equations Transforms Image resolution

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ROLE OF SIMULATION IN RAPID PROTOTYPING FOR CONCEPT DEVELOPMENT

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NAVAL ENGINEERS JOURNAL 1991年第3期103卷 204-211页

作者： KING, JF BARTON, DE J. Fred King:is the manager of the Advanced Technology Department for Unisys in Reston Virginia. He earned his Ph.D. in mathematics from the University of Houston in 1977. He has been principal investigator of research projects in knowledge engineering pattern recognition and heuristic problem-solving. Efforts include the development of a multi-temporal multispectral classifier for identifying graincrops using LANDSAT satellite imagery data for NASA. Also as a member of the research team for a NCI study with Baylor College of Medicine and NASA he helped develop techniques for detection of carcinoma using multispectral microphotometer scans of lung tissue. He established and became technical director of the AI Laboratory for Ford Aerospace where he developed expert scheduling modeling and knowledge acquisition systems for NASA. Since joining Unisys in 1985 he has led the development of object-oriented programming environments blackboard architectures data fusion techniques using neural networks and intelligent data base systems. Douglas E. Barton:is manager of Logistics Information Systems for Unisys in Reston Virginia. He earned his B.A. degree in computer science from the College of William and Mary in 1978 and did postgraduate work in London as a Drapers Company scholar. Since joining Unisys in 1981 his work has concentrated on program management and software engineering of large scale data base management systems and design and implementation of knowledge-based systems in planning and logistics. As chairman of the Logistics Data Subcommittee of the National Security Industrial Association (NSIA) he led an industry initiative which examined concepts in knowledge-based systems in military logistics. His responsibilities also include evaluation development and tailoring of software engineering standards and procedures for data base and knowledge-based systems. He is currently program manager of the Navigation Information Management System which provides support to the Fleet Ballistic Missile Progr

A valuable technique during concept development is rapid prototyping of software for key design components. This approach is particularly useful when the optimum design approach is not readily apparent or several known alternatives need to be rapidly evaluated. A problem inherent in rapid prototyping is the lack of a "target system" with which to interface. Some alternatives are to develop test driver libraries, integrate the prototype with an existing working simulator, or build one for the specific problem. This paper presents a unique approach to concept development using rapid prototyping for concept development and scenario-based simulation for concept verification. The rapid prototyping environment, derived from artificial intelligence technology, is based on a blackboard architecture. The rapid prototype simulation capability is provided through an object-oriented modeling environment. It is shown how both simulation and blackboard technologies are used collectively to rapidly gain insight into a tenacious problem. A specific example will be discussed where this approach was used to evolve the logic of a mission controller for an autonomous underwater vehicle.

关键词： Military Engineering

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heuristic Search for New Microcircuit Structures: An Application of Artificial Intelligence

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AI Magazine 1982年第3期3卷

作者： Douglas B. Lenat William R. Sutherland James Gibbons Heuristic Programming Project Department of Computer Science Stanford University Sutherland Sproull & Associates Inc Stanford Electronics Laboratory Stanford University

Summary Eurisko is an AI program that learns by discovery We are applying Eurisko to the task of inventing new kinds of three-dimensional microelectronic devices that can then be fabricated using recently developed laser recrystallization techniques Three experiments have been conducted, and some novel designs and design rules have emerged.

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THE PROSPECT OF AN UNDER WA TER NA VAL ROBOT

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Naval Engineers Journal 1980年第1期92卷 65-72页

作者： DIXON, JOHN K. JOHNSON, HERBERT A. SLAGLE, JAMES R. Dr. John K. Dixon was born on 1 December 1934 in Detroit. Mich. He received his B.S. degree in Electrical Engineering from Lawrence Institute of Technology in 1957 his M.B.A. degree from Wayne State University in 1964 his M.S. degree in Physics from the University of California at Davis in 1967 and his Ph.D. degree in Computer Science from the University of California at Livermore in 1970. In 1957 he was employed by the Chrysler Missile Division Warren Mich. where he designed circuits for the Redstoneand Jupitermissiles. In 1959 he joined the Staff of the Bendix Research Laboratory Southfield Mich. where he designed equipment for missile guidance systems and aircraft blind landing systems. From 1965 until 1968 he was a Research Assistant in the Artificial Intelligence Group Lawrence Radiation Laboratory. Livermore Calif at which time he left to join the Heuristics Laboratory of the National Institutes of Health Bethesda Md. as a Computer Scientist. In 1974 he moved to the Computer Science Laboratory at the Naval Research Laboratory. Washington D.C. where he is currently employed on various Research Projects. Mr. Herbert A. Johnson graduated from the U.S. Coast Guard Academy and later continued his graduate studies at Massachusetts Institute of Technology and Purdue University. receiving his M.S. degree in Electrical Engineering from the latter. He is presently a Captain in the U.S. Coast Guard Reserve and Head of the Ocean Instrumentation Branch. Ocean Technology Division Naval Research Laboratory (NRL). Prior to joining NRL in 1974 he was employed on various marine systems projects at Honeywell and on Polarisinstrumentation at Interstate Electronics a company he assisted in founding in 1956. He is a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE). Dr. James R. Slagle received his M.S. and Ph.D. degrees from Massachusetts Institute of Technology and was the recipient of an Outstanding Blind Student Award for 1959 which was presented to him by President Dwight D.

This paper explores the concept of an underwater robot manipulator mounted on an unmanned submersible for the purpose of doing some undersea tasks of interest to the U.S. Navy. The robot concept is compared with other methods of doing work underwater and its strengths and weaknesses are enumerated. Such a robot would be able to do only simple, well‐defined tasks, but it would probably be the most economical way of doing those jobs which are within its competence. The jobs which such a device might be able to do are listed and evaluated in terms of how easy or difficult they are for a robot to do. From this analysis some conclusions are drawn about what capabilities are needed in such a robot. It is concluded that speed of operation is not critical (In contrast to robots which are intended for industrial jobs), but that the ability to cope with unexpected conditions and to recover from mistakes is very important. Next, existing robot technology and past research***are discussed and evaluated in terms of the needs of an underwater naval robot. Gaps in the technology are identified, and, finally, me suggestions for research are given. © 1980 American Society of Naval Engineers

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