Model Based Self Supervision For Fine Grained Image Understanding
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Model Based Self Supervision For Fine Grained Image Understanding
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Author : Tanner Schmidt
language : en
Publisher:
Release Date : 2019
Model Based Self Supervision For Fine Grained Image Understanding written by Tanner Schmidt and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.
In order to enable robots that perform tasks capably, efficiently, and safely in dynamic environments, we'll need vision systems that are adaptable and can reliably provide detailed and accurate information about the world around the robot. Generative model-based methods are well suited to these demands, as generative models are portable (they are equally valid in many different environments), modular (they can be dynamically combined with other models), and interpretable (via likelihood functions and explicitly parameterized state spaces). For robotics applications, these properties give model-based vision an advantage over the currently dominant deep learning paradigm in computer vision. However, generative models are limited by the curse of dimensionality and data association ambiguity, and are thus plagued by a lack of robustness which is an impediment to successful deployment in robotic systems. This dissertation advances the argument that the strengths and weaknesses of generative model-based vision and discriminative learning-based vision are largely complementary, and can therefore be used to mutual advantage. Specifically, we'll show that generative models can be employed to automate the process of labeling data for supervised training of deep neural networks, demonstrating the benefit to deep learning offered by model-based vision. Then, we'll show that deep neural networks trained to recognize parts of generative models can be used to help resolve ambiguous data association and thus enhance the robustness of state estimation, demonstrating the benefits deep learning can bring back to model-based vision. Overall, we lay out a vision for future development of highly capable robot perception systems in which machine learning expands the envelope of situations in which generative model-based techniques are reliably applicable, and the generative model-based techniques return the favor by providing labels for further training of the network.
Fine Grained Image Analysis Modern Approaches
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Author : Xiu-Shen Wei
language : en
Publisher: Springer Nature
Release Date : 2023-07-03
Fine Grained Image Analysis Modern Approaches written by Xiu-Shen Wei and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-03 with Computers categories.
This book provides a comprehensive overview of the fine-grained image analysis research and modern approaches based on deep learning, spanning the full range of topics needed for designing operational fine-grained image systems. The author begins by providing detailed background information on FGIA, focusing on recognition and retrieval. The author also provides the fundamentals of convolutional neural networks to further make it easier for readers to understand the technical content in the book. The book introduces the main technical paradigms, technological developments, and representative approaches of fine-grained image recognition and fine-grained image retrieval. The author covers multiple popular research topics and includes cross-domain knowledge. The book also highlights advanced applications and topics for future research.
Computer Vision Eccv 2022
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Author : Shai Avidan
language : en
Publisher: Springer Nature
Release Date : 2022-10-22
Computer Vision Eccv 2022 written by Shai Avidan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-22 with Computers categories.
The 39-volume set, comprising the LNCS books 13661 until 13699, constitutes the refereed proceedings of the 17th European Conference on Computer Vision, ECCV 2022, held in Tel Aviv, Israel, during October 23–27, 2022. The 1645 papers presented in these proceedings were carefully reviewed and selected from a total of 5804 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation.
Multimedia Modeling
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Author : Stevan Rudinac
language : en
Publisher: Springer Nature
Release Date :
Multimedia Modeling written by Stevan Rudinac and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Objects Data Ai
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Author : Reeshabh Choudhary
language : en
Publisher: Reeshabh Choudhary
Release Date : 2023-11-10
Objects Data Ai written by Reeshabh Choudhary and has been published by Reeshabh Choudhary this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-10 with Computers categories.
This book is about uncovering a journey of how Software programming evolved and AI based technologies came into foray. This book tries to connect the dots for a new programmer, starting on his/her journey into the software development world. With so many technologies evolving around every single day, with new breaches in innovation in the field of AI/ML or Data Science, which gets the job done in a whisker, as programmers we tend to think, where do we stand? The journey or even the thought of making sense of everything around us can be quite overwhelming. From the days of C/C++ programming to Java/C#/JavaScript and Python/MATLAB/R, programming has exponentially evolved. And so, does the computational ability of computers, which also helped in faster execution of these programs, but also to extraction of Information from the data generated via the applications developed by these programs. In this digital age, everything seems to be connected and yet we sweat making sense of all these connections. In the interconnected digital age, understanding the connections between various technologies can be challenging. The book aims to bridge some of these gaps by providing readers with a foundational understanding of how programming, data, and machine learning are interconnected. By grasping these fundamentals, software developers can connect the dots according to their specific requirements.
Document Analysis Systems
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Author : Xiang Bai
language : en
Publisher: Springer Nature
Release Date : 2020-08-14
Document Analysis Systems written by Xiang Bai and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-14 with Computers categories.
This book constitutes the refereed proceedings of the 14th IAPR International Workshop on Document Analysis Systems, DAS 2020, held in Wuhan, China, in July 2020. The 40 full papers presented in this book were carefully reviewed and selected from 57 submissions. The papers are grouped in the following topical sections: character and text recognition; document image processing; segmentation and layout analysis; word embedding and spotting; text detection; and font design and classification. Due to the Corona pandemic the conference was held as a virtual event .
Computational Mathematics Modeling In Cancer Analysis
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Author : Wenjian Qin
language : en
Publisher: Springer Nature
Release Date : 2022-09-22
Computational Mathematics Modeling In Cancer Analysis written by Wenjian Qin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-22 with Computers categories.
This book constitutes the proceedings of the First Workshop on Computational Mathematics Modeling in Cancer Analysis (CMMCA2022), held in conjunction with MICCAI 2022, in Singapore in September 2022. Due to the COVID-19 pandemic restrictions, the CMMCA2022 was held virtually. DALI 2022 accepted 15 papers from the 16 submissions that were reviewed. A major focus of CMMCA2022 is to identify new cutting-edge techniques and their applications in cancer data analysis in response to trends and challenges in theoretical, computational and applied aspects of mathematics in cancer data analysis.
Human Centric Visual Analysis With Deep Learning
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Author : Liang Lin
language : en
Publisher: Springer Nature
Release Date : 2019-11-13
Human Centric Visual Analysis With Deep Learning written by Liang Lin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-13 with Computers categories.
This book introduces the applications of deep learning in various human centric visual analysis tasks, including classical ones like face detection and alignment and some newly rising tasks like fashion clothing parsing. Starting from an overview of current research in human centric visual analysis, the book then presents a tutorial of basic concepts and techniques of deep learning. In addition, the book systematically investigates the main human centric analysis tasks of different levels, ranging from detection and segmentation to parsing and higher-level understanding. At last, it presents the state-of-the-art solutions based on deep learning for every task, as well as providing sufficient references and extensive discussions. Specifically, this book addresses four important research topics, including 1) localizing persons in images, such as face and pedestrian detection; 2) parsing persons in details, such as human pose and clothing parsing, 3) identifying and verifying persons, such as face and human identification, and 4) high-level human centric tasks, such as person attributes and human activity understanding. This book can serve as reading material and reference text for academic professors / students or industrial engineers working in the field of vision surveillance, biometrics, and human-computer interaction, where human centric visual analysis are indispensable in analysing human identity, pose, attributes, and behaviours for further understanding.
Image Analysis And Processing Iciap 2023
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Author : Gian Luca Foresti
language : en
Publisher: Springer Nature
Release Date : 2023-09-04
Image Analysis And Processing Iciap 2023 written by Gian Luca Foresti and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-04 with Computers categories.
This two-volume set LNCS 14233-14234 constitutes the refereed proceedings of the 22nd International Conference on Image Analysis and Processing, ICIAP 2023, held in Udine, Italy, during September 11–15, 2023. The 85 full papers presented together with 7 short papers were carefully reviewed and selected from 144 submissions. The conference focuses on video analysis and understanding; pattern recognition and machine learning; deep learning; multi-view geometry and 3D computer vision; image analysis, detection and recognition; multimedia; biomedical and assistive technology; digital forensics and biometrics; image processing for cultural heritage; and robot vision.
Information Processing In Medical Imaging
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Author : Aasa Feragen
language : en
Publisher: Springer Nature
Release Date : 2021-06-20
Information Processing In Medical Imaging written by Aasa Feragen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-20 with Computers categories.
This book constitutes the proceedings of the 27th International Conference on Information Processing in Medical Imaging, IPMI 2021, which was held online during June 28-30, 2021. The conference was originally planned to take place in Bornholm, Denmark, but changed to a virtual format due to the COVID-19 pandemic. The 59 full papers presented in this volume were carefully reviewed and selected from 200 submissions. They were organized in topical sections as follows: registration; causal models and interpretability; generative modelling; shape; brain connectivity; representation learning; segmentation; sequential modelling; learning with few or low quality labels; uncertainty quantification and generative modelling; and deep learning.