How Humans Recognize Objects: Segmentation, Categorization and Individual Identification

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Publisher : Frontiers Media SA
ISBN 13 : 2889199401
Total Pages : 267 pages
Book Rating : 4.8/5 (891 download)

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Book Synopsis How Humans Recognize Objects: Segmentation, Categorization and Individual Identification by : Chris Fields

Download or read book How Humans Recognize Objects: Segmentation, Categorization and Individual Identification written by Chris Fields and published by Frontiers Media SA. This book was released on 2016-08-18 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: Human beings experience a world of objects: bounded entities that occupy space and persist through time. Our actions are directed toward objects, and our language describes objects. We categorize objects into kinds that have different typical properties and behaviors. We regard some kinds of objects – each other, for example – as animate agents capable of independent experience and action, while we regard other kinds of objects as inert. We re-identify objects, immediately and without conscious deliberation, after days or even years of non-observation, and often following changes in the features, locations, or contexts of the objects being re-identified. Comparative, developmental and adult observations using a variety of approaches and methods have yielded a detailed understanding of object detection and recognition by the visual system and an advancing understanding of haptic and auditory information processing. Many fundamental questions, however, remain unanswered. What, for example, physically constitutes an “object”? How do specific, classically-characterizable object boundaries emerge from the physical dynamics described by quantum theory, and can this emergence process be described independently of any assumptions regarding the perceptual capabilities of observers? How are visual motion and feature information combined to create object information? How are the object trajectories that indicate persistence to human observers implemented, and how are these trajectory representations bound to feature representations? How, for example, are point-light walkers recognized as single objects? How are conflicts between trajectory-driven and feature-driven identifications of objects resolved, for example in multiple-object tracking situations? Are there separate “what” and “where” processing streams for haptic and auditory perception? Are there haptic and/or auditory equivalents of the visual object file? Are there equivalents of the visual object token? How are object-identification conflicts between different perceptual systems resolved? Is the common assumption that “persistent object” is a fundamental innate category justified? How does the ability to identify and categorize objects relate to the ability to name and describe them using language? How are features that an individual object had in the past but does not have currently represented? How are categorical constraints on how objects move or act represented, and how do such constraints influence categorization and the re-identification of individuals? How do human beings re-identify objects, including each other, as persistent individuals across changes in location, context and features, even after gaps in observation lasting months or years? How do human capabilities for object categorization and re-identification over time relate to those of other species, and how do human infants develop these capabilities? What can modeling approaches such as cognitive robotics tell us about the answers to these questions? Primary research reports, reviews, and hypothesis and theory papers addressing questions relevant to the understanding of perceptual object segmentation, categorization and individual identification at any scale and from any experimental or modeling perspective are solicited for this Research Topic. Papers that review particular sets of issues from multiple disciplinary perspectives or that advance integrative hypotheses or models that take data from multiple experimental approaches into account are especially encouraged.

How Humans Recognize Objects: Segmentation, Categorization and Individual Identification

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Author :
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (136 download)

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Book Synopsis How Humans Recognize Objects: Segmentation, Categorization and Individual Identification by :

Download or read book How Humans Recognize Objects: Segmentation, Categorization and Individual Identification written by and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Human beings experience a world of objects: bounded entities that occupy space and persist through time. Our actions are directed toward objects, and our language describes objects. We categorize objects into kinds that have different typical properties and behaviors. We regard some kinds of objects - each other, for example - as animate agents capable of independent experience and action, while we regard other kinds of objects as inert. We re-identify objects, immediately and without conscious deliberation, after days or even years of non-observation, and often following changes in the features, locations, or contexts of the objects being re-identified. Comparative, developmental and adult observations using a variety of approaches and methods have yielded a detailed understanding of object detection and recognition by the visual system and an advancing understanding of haptic and auditory information processing. Many fundamental questions, however, remain unanswered. What, for example, physically constitutes an "object"? How do specific, classically-characterizable object boundaries emerge from the physical dynamics described by quantum theory, and can this emergence process be described independently of any assumptions regarding the perceptual capabilities of observers? How are visual motion and feature information combined to create object information? How are the object trajectories that indicate persistence to human observers implemented, and how are these trajectory representations bound to feature representations? How, for example, are point-light walkers recognized as single objects? How are conflicts between trajectory-driven and feature-driven identifications of objects resolved, for example in multiple-object tracking situations? Are there separate "what" and "where" processing streams for haptic and auditory perception? Are there haptic and/or auditory equivalents of the visual object file? Are there equivalents of the visual object token? How are object-identification conflicts between different perceptual systems resolved? Is the common assumption that "persistent object" is a fundamental innate category justified? How does the ability to identify and categorize objects relate to the ability to name and describe them using language? How are features that an individual object had in the past but does not have currently represented? How are categorical constraints on how objects move or act represented, and how do such constraints influence categorization and the re-identification of individuals? How do human beings re-identify objects, including each other, as persistent individuals across changes in location, context and features, even after gaps in observation lasting months or years? How do human capabilities for object categorization and re-identification over time relate to those of other species, and how do human infants develop these capabilities? What can modeling approaches such as cognitive robotics tell us about the answers to these questions? Primary research reports, reviews, and hypothesis and theory papers addressing questions relevant to the understanding of perceptual object segmentation, categorization and individual identification at any scale and from any experimental or modeling perspective are solicited for this Research Topic. Papers that review particular sets of issues from multiple disciplinary perspectives or that advance integrative hypotheses or models that take data from multiple experimental approaches into account are especially encouraged.

Object Categorization

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Author :
Publisher : Cambridge University Press
ISBN 13 : 0521887380
Total Pages : 553 pages
Book Rating : 4.5/5 (218 download)

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Book Synopsis Object Categorization by : Sven J. Dickinson

Download or read book Object Categorization written by Sven J. Dickinson and published by Cambridge University Press. This book was released on 2009-09-07 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: A unique multidisciplinary perspective on the problem of visual object categorization.

Object Categorization

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Author :
Publisher : Now Publishers Inc
ISBN 13 : 1933019131
Total Pages : 110 pages
Book Rating : 4.9/5 (33 download)

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Book Synopsis Object Categorization by : Axel Pinz

Download or read book Object Categorization written by Axel Pinz and published by Now Publishers Inc. This book was released on 2006 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt: This article presents foundations, original research and trends in the field of object categorization by computer vision methods. The research goals in object categorization are to detect objects in images and to determine the object's categories. Categorization aims for the recognition of generic classes of objects, and thus has also been termed 'generic object recognition'. This is in contrast to the recognition of specific, individual objects. While humans are usually better in generic than in specific recognition, categorization is much harder to achieve for today's computer architectures.

Computer Vision - ECCV 2008

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Publisher : Springer
ISBN 13 : 3540886931
Total Pages : 891 pages
Book Rating : 4.5/5 (48 download)

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Book Synopsis Computer Vision - ECCV 2008 by : David Forsyth

Download or read book Computer Vision - ECCV 2008 written by David Forsyth and published by Springer. This book was released on 2008-10-11 with total page 891 pages. Available in PDF, EPUB and Kindle. Book excerpt: Welcome to the 2008EuropeanConference onComputer Vision. These proce- ings are the result of a great deal of hard work by many people. To produce them, a total of 871 papers were reviewed. Forty were selected for oral pres- tation and 203 were selected for poster presentation, yielding acceptance rates of 4.6% for oral, 23.3% for poster, and 27.9% in total. Weappliedthreeprinciples.First,sincewehadastronggroupofAreaChairs, the ?nal decisions to accept or reject a paper rested with the Area Chair, who wouldbeinformedbyreviewsandcouldactonlyinconsensuswithanotherArea Chair. Second, we felt that authors were entitled to a summary that explained how the Area Chair reached a decision for a paper. Third, we were very careful to avoid con?icts of interest. Each paper was assigned to an Area Chair by the Program Chairs, and each Area Chair received a pool of about 25 papers. The Area Chairs then identi?ed and rankedappropriatereviewersfor eachpaper in their pool, and a constrained optimization allocated three reviewers to each paper. We are very proud that every paper received at least three reviews. At this point, authors were able to respond to reviews. The Area Chairs then needed to reach a decision. We used a series of procedures to ensure careful review and to avoid con?icts of interest. ProgramChairs did not submit papers. The Area Chairs were divided into three groups so that no Area Chair in the group was in con?ict with any paper assigned to any Area Chair in the group.

Object Recognition Of Digital Images In Wavelet Neural Network

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Author :
Publisher : Archers & Elevators Publishing House
ISBN 13 : 9386501244
Total Pages : pages
Book Rating : 4.3/5 (865 download)

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Book Synopsis Object Recognition Of Digital Images In Wavelet Neural Network by : Arul Murugan R

Download or read book Object Recognition Of Digital Images In Wavelet Neural Network written by Arul Murugan R and published by Archers & Elevators Publishing House. This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Encyclopedia of Perception

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Publisher : SAGE
ISBN 13 : 1412940818
Total Pages : 1281 pages
Book Rating : 4.4/5 (129 download)

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Book Synopsis Encyclopedia of Perception by : E. Bruce Goldstein

Download or read book Encyclopedia of Perception written by E. Bruce Goldstein and published by SAGE. This book was released on 2009-10-15 with total page 1281 pages. Available in PDF, EPUB and Kindle. Book excerpt: Because of the ease with which we perceive, many people see perception as something that "just happens." However, even seemingly simple perceptual experiences involve complex underlying mechanisms, which are often hidden from our conscious experience. These mechanisms are being investigated by researchers and theorists in fields such as psychology, cognitive science, neuroscience, computer science, and philosophy. A few examples of the questions posed by these investigations are, What do infants perceive? How does perception develop? What do perceptual disorders reveal about normal functioning? How can information from one sense, such as hearing, be affected by information from another sense, such as vision? How is the information from all of our senses combined to result in our perception of a coherent environment? What are some practical outcomes of basic research in perception? These are just a few of the questions this encyclopedia will consider, as it presents a comprehensive overview of the field of perception for students, researchers, and professionals in psychology, the cognitive sciences, neuroscience, and related medical disciplines such as neurology and ophthalmology.

Deep Learning in Object Recognition, Detection, and Segmentation

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Author :
Publisher :
ISBN 13 : 9781680831177
Total Pages : 165 pages
Book Rating : 4.8/5 (311 download)

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Book Synopsis Deep Learning in Object Recognition, Detection, and Segmentation by : Xiaogang Wang

Download or read book Deep Learning in Object Recognition, Detection, and Segmentation written by Xiaogang Wang and published by . This book was released on 2016 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt: As a major breakthrough in artificial intelligence, deep learning has achieved very impressive success in solving grand challenges in many fields including speech recognition, natural language processing, computer vision, image and video processing, and multimedia. This article provides a historical overview of deep learning and focus on its applications in object recognition, detection, and segmentation, which are key challenges of computer vision and have numerous applications to images and videos. The discussed research topics on object recognition include image classification on ImageNet, face recognition, and video classification. The detection part covers general object detection on ImageNet, pedestrian detection, face landmark detection (face alignment), and human landmark detection (pose estimation). On the segmentation side, the article discusses the most recent progress on scene labeling, semantic segmentation, face parsing, human parsing and saliency detection. Object recognition is considered as whole-image classification, while detection and segmentation are pixelwise classification tasks. Their fundamental differences will be discussed in this article. Fully convolutional neural networks and highly efficient forward and backward propagation algorithms specially designed for pixelwise classification task will be introduced. The covered application domains are also much diversified. Human and face images have regular structures, while general object and scene images have much more complex variations in geometric structures and layout. Videos include the temporal dimension. Therefore, they need to be processed with different deep models. All the selected domain applications have received tremendous attentions in the computer vision and multimedia communities. Through concrete examples of these applications, we explain the key points which make deep learning outperform conventional computer vision systems. (1) Different than traditional pattern recognition systems, which heavily rely on manually designed features, deep learning automatically learns hierarchical feature representations from massive training data and disentangles hidden factors of input data through multi-level nonlinear mappings. (2) Different than existing pattern recognition systems which sequentially design or train their key components, deep learning is able to jointly optimize all the components and crate synergy through close interactions among them. (3) While most machine learning models can be approximated with neural networks with shallow structures, for some tasks, the expressive power of deep models increases exponentially as their architectures go deep. Deep models are especially good at learning global contextual feature representation with their deep structures. (4) Benefitting from the large learning capacity of deep models, some classical computer vision challenges can be recast as high-dimensional data transform problems and can be solved from new perspectives. Finally, some open questions and future works regarding to deep learning in object recognition, detection, and segmentation will be discussed.

Intelligent Systems

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Publisher : Springer Nature
ISBN 13 : 303121689X
Total Pages : 686 pages
Book Rating : 4.0/5 (312 download)

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Book Synopsis Intelligent Systems by : João Carlos Xavier-Junior

Download or read book Intelligent Systems written by João Carlos Xavier-Junior and published by Springer Nature. This book was released on 2022-11-18 with total page 686 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNAI 13653 and 13654 constitutes the refereed proceedings of the 11th Brazilian Conference on Intelligent Systems, BRACIS 2022, which took place in Campinas, Brazil, in November/December 2022. The 89 papers presented in the proceedings were carefully reviewed and selected from 225 submissions. The conference deals with theoretical aspects and applications of artificial and computational intelligence.

Medial measures for recognition, mapping and categorization

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Author :
Publisher : McGill University
ISBN 13 :
Total Pages : 207 pages
Book Rating : 4./5 ( download)

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Book Synopsis Medial measures for recognition, mapping and categorization by : Morteza Rezanejad

Download or read book Medial measures for recognition, mapping and categorization written by Morteza Rezanejad and published by McGill University. This book was released on with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt: Visual shape analysis plays a fundamental role in perception by man and by computer, allowing for inferences about properties of objects and scenes in the physical world. Mathematical approaches to describing visual form can benefit from the use of representations that simultaneously capture properties of an object's outline as well as its interior. Motivated by the success of medial models, this doctoral thesis revisits a quantity related to medial axis computations, the average outward flux of the gradient of the Euclidean distance function from a boundary, and then addresses three distinct problems using this measure. First, I consider the problem of view sphere partitioning for view-based object recognition from sparse views. View-based 3D object recognition requires a selection of model object views against which to match a query view. Ideally, for this to be computationally efficient, such a selection should be sparse. To address this problem, I introduce a novel hierarchical partitioning of the view sphere into regions within which the silhouette of a model object is qualitatively unchanged. To achieve this, I propose a part-based abstraction of a skeleton, as a graph, dubbed the Flux Graph, which allows for views to be grouped. Next, I consider the problem of mapping an initially-unknown 2D environment from possibly noisy sensed samples via an on-line procedure which robustly computes a retraction of its boundaries to obtain a topological representation. Here I motto an algorithm that allows for online map construction with loop closure. I demonstrate that the proposed method allows the robot to localize itself on a partially constructed map to calculate a path to unexplored parts of the environment (frontiers), to compute a robust terminating condition when the robot has fully explored the environment, and finally to achieve loop closure detection. I also show that the resulting map is stable under disturbances to the sensed boundary, and to variations in starting locations for exploration. Finally, I consider the problem of scene categorization from complex line drawings. In the context of human vision, we show that local ribbon symmetry between neighboring pairs of contours facilitates the categorization of complex real-world environments by human observers. In the context of computer vision, I demonstrate a high level of performance in the problem of convolutional neural network-based recognition of natural scenes from line drawings, even in the absence of color, texture and shading information.

Advances in Emerging Trends and Technologies

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Publisher : Springer Nature
ISBN 13 : 3030320227
Total Pages : 557 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Advances in Emerging Trends and Technologies by : Miguel Botto-Tobar

Download or read book Advances in Emerging Trends and Technologies written by Miguel Botto-Tobar and published by Springer Nature. This book was released on 2019-10-12 with total page 557 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 1st International Conference on Advances in Emerging Trends and Technologies (ICAETT 2019), held in Quito, Ecuador, on 29–31 May 2019, jointly organized by Universidad Tecnológica Israel, Universidad Técnica del Norte, and Instituto Tecnológico Superior Rumiñahui, and supported by SNOTRA. ICAETT 2019 brought together top researchers and practitioners working in different domains of computer science to share their expertise and to discuss future developments and potential collaborations. Presenting high-quality, peer-reviewed papers, the book discusses the following topics: Technology Trends Electronics Intelligent Systems Machine Vision Communication Security e-Learning e-Business e-Government and e-Participation

Computational Intelligence in Data Mining

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Publisher : Springer Nature
ISBN 13 : 9811694478
Total Pages : 757 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Computational Intelligence in Data Mining by : Janmenjoy Nayak

Download or read book Computational Intelligence in Data Mining written by Janmenjoy Nayak and published by Springer Nature. This book was released on 2022-05-06 with total page 757 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses different methods and techniques of integration for enhancing the overall goal of data mining. The book is a collection of high-quality peer-reviewed research papers presented in the Sixth International Conference on Computational Intelligence in Data Mining (ICCIDM 2021) held at Aditya Institute of Technology and Management, Tekkali, Andhra Pradesh, India, during December 11–12, 2021. The book addresses the difficulties and challenges for the seamless integration of two core disciplines of computer science, i.e., computational intelligence and data mining. The book helps to disseminate the knowledge about some innovative, active research directions in the field of data mining, machine and computational intelligence, along with some current issues and applications of related topics.

Recognition of Humans and Their Activities Using Video

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Publisher : Springer Nature
ISBN 13 : 303102236X
Total Pages : 171 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Recognition of Humans and Their Activities Using Video by : Rama Chellappa

Download or read book Recognition of Humans and Their Activities Using Video written by Rama Chellappa and published by Springer Nature. This book was released on 2022-05-31 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: The recognition of humans and their activities from video sequences is currently a very active area of research because of its applications in video surveillance, design of realistic entertainment systems, multimedia communications, and medical diagnosis. In this lecture, we discuss the use of face and gait signatures for human identification and recognition of human activities from video sequences. We survey existing work and describe some of the more well-known methods in these areas. We also describe our own research and outline future possibilities. In the area of face recognition, we start with the traditional methods for image-based analysis and then describe some of the more recent developments related to the use of video sequences, 3D models, and techniques for representing variations of illumination. We note that the main challenge facing researchers in this area is the development of recognition strategies that are robust to changes due to pose, illumination, disguise, and aging. Gait recognition is a more recent area of research in video understanding, although it has been studied for a long time in psychophysics and kinesiology. The goal for video scientists working in this area is to automatically extract the parameters for representation of human gait. We describe some of the techniques that have been developed for this purpose, most of which are appearance based. We also highlight the challenges involved in dealing with changes in viewpoint and propose methods based on image synthesis, visual hull, and 3D models. In the domain of human activity recognition, we present an extensive survey of various methods that have been developed in different disciplines like artificial intelligence, image processing, pattern recognition, and computer vision. We then outline our method for modeling complex activities using 2D and 3D deformable shape theory. The wide application of automatic human identification and activity recognition methods will require the fusion of different modalities like face and gait, dealing with the problems of pose and illumination variations, and accurate computation of 3D models. The last chapter of this lecture deals with these areas of future research.

Social Data Analytics

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Publisher : CRC Press
ISBN 13 : 100064460X
Total Pages : 251 pages
Book Rating : 4.0/5 (6 download)

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Book Synopsis Social Data Analytics by : Amin Beheshti

Download or read book Social Data Analytics written by Amin Beheshti and published by CRC Press. This book was released on 2022-08-01 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an introduction to social data analytics along with its challenges and opportunities in the age of Big Data and Artificial Intelligence. It focuses primarily on concepts, techniques and methods for organizing, curating, processing, analyzing, and visualizing big social data: from text to image and video analytics. It provides novel techniques in storytelling with social data to facilitate the knowledge and fact discovery. The book covers a large body of knowledge that will help practitioners and researchers in understanding the underlying concepts, problems, methods, tools and techniques involved in modern social data analytics. It also provides real-world applications of social data analytics, including: Sales and Marketing, Influence Maximization, Situational Awareness, customer success and Segmentation, and performance analysis of the industry. It provides a deep knowledge in social data analytics by comprehensively classifying the current state of research, by describing in-depth techniques and methods, and by highlighting future research directions. Lecturers will find a wealth of material to choose from for a variety of courses, ranging from undergraduate courses in data science to graduate courses in data analytics.

Sociomateriality in Children with Typical and/or Atypical Development

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Author :
Publisher : Frontiers Media SA
ISBN 13 : 2889664341
Total Pages : 138 pages
Book Rating : 4.8/5 (896 download)

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Book Synopsis Sociomateriality in Children with Typical and/or Atypical Development by : Antonio Iannaccone

Download or read book Sociomateriality in Children with Typical and/or Atypical Development written by Antonio Iannaccone and published by Frontiers Media SA. This book was released on 2021-02-03 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Pattern Recognition

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Publisher : Springer
ISBN 13 : 3319458868
Total Pages : 452 pages
Book Rating : 4.3/5 (194 download)

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Book Synopsis Pattern Recognition by : Bodo Rosenhahn

Download or read book Pattern Recognition written by Bodo Rosenhahn and published by Springer. This book was released on 2016-08-26 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 38th German Conference on Pattern Recognition, GCPR 2016, held in Hannover, Germany, in September 2016. The 36 revised full papers presented were carefully reviewed and selected from 85 submissions. The papers are organized in topical sections on image processing, learning, optimization, segmentation, applications, image analysis, motion and tracking.

Artificial Intelligence and Data Science

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Publisher : Springer Nature
ISBN 13 : 3031213858
Total Pages : 553 pages
Book Rating : 4.0/5 (312 download)

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Book Synopsis Artificial Intelligence and Data Science by : Ashwani Kumar

Download or read book Artificial Intelligence and Data Science written by Ashwani Kumar and published by Springer Nature. This book was released on 2022-12-13 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes selected papers presented at the First International Conference on Artificial Intelligence and Data Science, ICAIDS 2021, held in Hyderabad, India, in December 2021. The 43 papers presented in this volume were thoroughly reviewed and selected from the 195 submissions. They focus on topics of artificial intelligence for intelligent applications and data science for emerging technologies.