Download or read book Unsupervised Learning of 3D Objects in the Wild written by Shangzhe Wu and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Investigations of Factors that Affect Unsupervised Learning of 3D Object Representations written by Moqian Tian and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Humans have an amazing ability to learn to recognize objects across transformations that present very different retinal stimuli, such as changes in size, illumination, and rotations in space. Such identity-preserving image transformations (DiCarlo, Zoccolan, & Rust, 2012) put extraordinary pressure on our visual system because the computations needed to assign vastly different 2D images of an object to the same identity are non-trivial. However, both behavioral (Biederman & Cooper, 1991a, 1991b; Fiser & Biederman, 1995; Potter, 1976; Thorpe, Fize, & Marlot, 1996) and neural (Hung, Kreiman, Poggio, & DiCarlo, 2005) evidence suggest that the visual system solves this problem accurately and rapidly. While rotations in the image plane preserve the visible features, rotations in-depth may reveal new features of an opaque object and thus present the most difficult transformation for the visual system to resolve, because the resulting 2D image from an in-depth rotation may be unrecoverable from the original image. Thus, understanding how people achieve viewpoint invariance, or the ability to recognize objects from different views and rotations, is key to understanding the visual object recognition system. There is a general consensus that learning is an important component for developing viewpoint invariant object recognition (Logothetis and Pauls, 1992; Tarr and Pinker, 1989). Many studies show that learning can occur in an unsupervised way just from viewing example images of new objects (Edelman and Bulthoff, 1992; Tarr and Pinker, 1989). Two major theories regarding how the visual system achieves viewpoint invariance -- 3D-based theories (Biederman, 1987) and view-based theories (Ullman and Basri, 1989) -- recognize the importance of learning in achieving viewpoint invariant object recognition. However, they differ in what information is used during learning and what representation is consequently built. For example, view-based theories consider spatial and temporal continuities as necessary glue for linking multiple views of an object during unsupervised learning, but 3D-based theories consider feature information to be more important. They also differ on whether the object representation that is built after learning is 3D based or view based. To address these gaps in the published literature, I examined two core questions: What kind of spatial and temporal information in the visual input during unsupervised learning is critical for achieving viewpoint invariant recognition? And what kind of object representation is generated during the learning process? In Chapter 1, I will present a theoretical overview of the issues. Section 1 reviews theories and computational models of viewpoint invariant recognition, with a focus on the debate between 3D-based theories and view-based theories; Section 2 reviews psychophysical and neural evidence supporting each theory; and Section 3 discusses the predictions of the learning mechanisms of each of the competing theories. Chapter 2 presents results from a series of experiments that investigated the spatio-temporal information in the visual input during unsupervised learning that is key for learning the 3D structure of novel objects. Chapter 3 presents data from a series of experiments that examine how the format of the visual information during unsupervised learning affects learning the 3D structure of novel objects. Finally, in Chapter 4, I will discuss the theoretical implications of the findings presented in Chapters 2 & 3, and propose a new framework based on these results.
Download or read book Pattern Recognition and Computer Vision written by Huimin Ma and published by Springer Nature. This book was released on 2021-10-22 with total page 695 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 4-volume set LNCS 13019, 13020, 13021 and 13022 constitutes the refereed proceedings of the 4th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2021, held in Beijing, China, in October-November 2021. The 201 full papers presented were carefully reviewed and selected from 513 submissions. The papers have been organized in the following topical sections: Object Detection, Tracking and Recognition; Computer Vision, Theories and Applications, Multimedia Processing and Analysis; Low-level Vision and Image Processing; Biomedical Image Processing and Analysis; Machine Learning, Neural Network and Deep Learning, and New Advances in Visual Perception and Understanding.
Download or read book Unsupervised Learning for 3D Point Cloud Object Detection Using Roadside Dataset written by 吳泯駿 and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Computer Vision ECCV 2022 written by Shai Avidan and published by Springer Nature. This book was released on 2022-11-10 with total page 811 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book MultiMedia Modeling written by Stevan Rudinac and published by Springer Nature. This book was released on with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Artificial Neural Networks and Machine Learning ICANN 2023 written by Lazaros Iliadis and published by Springer Nature. This book was released on 2023-09-21 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 10-volume set LNCS 14254-14263 constitutes the proceedings of the 32nd International Conference on Artificial Neural Networks and Machine Learning, ICANN 2023, which took place in Heraklion, Crete, Greece, during September 26–29, 2023. The 426 full papers, 9 short papers and 9 abstract papers included in these proceedings were carefully reviewed and selected from 947 submissions. ICANN is a dual-track conference, featuring tracks in brain inspired computing on the one hand, and machine learning on the other, with strong cross-disciplinary interactions and applications.
Download or read book Computer Vision ECCV 2020 written by Andrea Vedaldi and published by Springer Nature. This book was released on 2020-11-15 with total page 836 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 30-volume set, comprising the LNCS books 12346 until 12375, constitutes the refereed proceedings of the 16th European Conference on Computer Vision, ECCV 2020, which was planned to be held in Glasgow, UK, during August 23-28, 2020. The conference was held virtually due to the COVID-19 pandemic. The 1360 revised papers presented in these proceedings were carefully reviewed and selected from a total of 5025 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.
Download or read book Data Engineering and Applications written by Jitendra Agrawal and published by Springer Nature. This book was released on with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Computer Vision ACCV 2022 written by Lei Wang and published by Springer Nature. This book was released on 2023-03-03 with total page 687 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 7-volume set of LNCS 13841-13847 constitutes the proceedings of the 16th Asian Conference on Computer Vision, ACCV 2022, held in Macao, China, December 2022. The total of 277 contributions included in the proceedings set was carefully reviewed and selected from 836 submissions during two rounds of reviewing and improvement. The papers focus on the following topics: Part I: 3D computer vision; optimization methods; Part II: applications of computer vision, vision for X; computational photography, sensing, and display; Part III: low-level vision, image processing; Part IV: face and gesture; pose and action; video analysis and event recognition; vision and language; biometrics; Part V: recognition: feature detection, indexing, matching, and shape representation; datasets and performance analysis; Part VI: biomedical image analysis; deep learning for computer vision; Part VII: generative models for computer vision; segmentation and grouping; motion and tracking; document image analysis; big data, large scale methods.
Download or read book Applied Systemic Studies written by Henry Selvaraj and published by Springer Nature. This book was released on 2023-03-21 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collection of a wide range of research papers that combine both the humanities and sciences in applied informatics. In particular, it is intended for readers interested in the fields of artificial intelligence, data science, virtual reality, and intelligent systems. Technologies and findings in artificial intelligence, data science, virtual reality, and intelligent systems are being used in all academic disciplines today. This book is a compilation of specific and advanced research findings from a wide range of research fields where they are being applied today. The papers included are based on those presented in August 2022 at the International Conference on Systems Engineering (ICSEng-Tokyo), a prestigious academic conference that has been held annually since 1974. The papers have been rigorously reviewed and selected by multiple peer reviewers.
Download or read book Advances in Neural Computation Machine Learning and Cognitive Research III written by Boris Kryzhanovsky and published by Springer Nature. This book was released on 2019-09-03 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes new theories and applications of artificial neural networks, with a special focus on answering questions in neuroscience, biology and biophysics and cognitive research. It covers a wide range of methods and technologies, including deep neural networks, large scale neural models, brain computer interface, signal processing methods, as well as models of perception, studies on emotion recognition, self-organization and many more. The book includes both selected and invited papers presented at the XXI International Conference on Neuroinformatics, held on October 7-11, 2019, in Dolgoprudny, a town in Moscow region, Russia.
Download or read book Pattern Recognition ICPR International Workshops and Challenges written by Alberto Del Bimbo and published by Springer Nature. This book was released on 2021-02-20 with total page 685 pages. Available in PDF, EPUB and Kindle. Book excerpt: This 8-volumes set constitutes the refereed of the 25th International Conference on Pattern Recognition Workshops, ICPR 2020, held virtually in Milan, Italy and rescheduled to January 10 - 11, 2021 due to Covid-19 pandemic. The 416 full papers presented in these 8 volumes were carefully reviewed and selected from about 700 submissions. The 46 workshops cover a wide range of areas including machine learning, pattern analysis, healthcare, human behavior, environment, surveillance, forensics and biometrics, robotics and egovision, cultural heritage and document analysis, retrieval, and women at ICPR2020.
Download or read book Computer Vision ECCV 2020 Workshops written by Adrien Bartoli and published by Springer Nature. This book was released on 2021-01-02 with total page 780 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 6-volume set, comprising the LNCS books 12535 until 12540, constitutes the refereed proceedings of 28 out of the 45 workshops held at the 16th European Conference on Computer Vision, ECCV 2020. The conference was planned to take place in Glasgow, UK, during August 23-28, 2020, but changed to a virtual format due to the COVID-19 pandemic. The 249 full papers, 18 short papers, and 21 further contributions included in the workshop proceedings were carefully reviewed and selected from a total of 467 submissions. The papers deal with diverse computer vision topics. Part II focusses on commands for autonomous vehicles; computer vision for ART analysis; sign language recognition, translation and production; visual inductive priors for data-efficient deep learning; 3D poses in the wild challenge; map-based localization for autonomous driving; recovering 6D object pose; and shape recovery from partial textured 3D scans.
Download or read book Uncertainty for Safe Utilization of Machine Learning in Medical Imaging and Clinical Image Based Procedures written by Hayit Greenspan and published by Springer Nature. This book was released on 2019-10-10 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the First International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2019, and the 8th International Workshop on Clinical Image-Based Procedures, CLIP 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019. For UNSURE 2019, 8 papers from 15 submissions were accepted for publication. They focus on developing awareness and encouraging research in the field of uncertainty modelling to enable safe implementation of machine learning tools in the clinical world. CLIP 2019 accepted 11 papers from the 15 submissions received. The workshops provides a forum for work centred on specific clinical applications, including techniques and procedures based on comprehensive clinical image and other data.
Download or read book Big Data Analytics for Large Scale Multimedia Search written by Stefanos Vrochidis and published by John Wiley & Sons. This book was released on 2019-05-28 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: A timely overview of cutting edge technologies for multimedia retrieval with a special emphasis on scalability The amount of multimedia data available every day is enormous and is growing at an exponential rate, creating a great need for new and more efficient approaches for large scale multimedia search. This book addresses that need, covering the area of multimedia retrieval and placing a special emphasis on scalability. It reports the recent works in large scale multimedia search, including research methods and applications, and is structured so that readers with basic knowledge can grasp the core message while still allowing experts and specialists to drill further down into the analytical sections. Big Data Analytics for Large-Scale Multimedia Search covers: representation learning, concept and event-based video search in large collections; big data multimedia mining, large scale video understanding, big multimedia data fusion, large-scale social multimedia analysis, privacy and audiovisual content, data storage and management for big multimedia, large scale multimedia search, multimedia tagging using deep learning, interactive interfaces for big multimedia and medical decision support applications using large multimodal data. Addresses the area of multimedia retrieval and pays close attention to the issue of scalability Presents problem driven techniques with solutions that are demonstrated through realistic case studies and user scenarios Includes tables, illustrations, and figures Offers a Wiley-hosted BCS that features links to open source algorithms, data sets and tools Big Data Analytics for Large-Scale Multimedia Search is an excellent book for academics, industrial researchers, and developers interested in big multimedia data search retrieval. It will also appeal to consultants in computer science problems and professionals in the multimedia industry.
Download or read book Artificial Neural Networks and Machine Learning ICANN 2021 written by Igor Farkaš and published by Springer Nature. This book was released on 2021-09-10 with total page 708 pages. Available in PDF, EPUB and Kindle. Book excerpt: The proceedings set LNCS 12891, LNCS 12892, LNCS 12893, LNCS 12894 and LNCS 12895 constitute the proceedings of the 30th International Conference on Artificial Neural Networks, ICANN 2021, held in Bratislava, Slovakia, in September 2021.* The total of 265 full papers presented in these proceedings was carefully reviewed and selected from 496 submissions, and organized in 5 volumes. In this volume, the papers focus on topics such as generative neural networks, graph neural networks, hierarchical and ensemble models, human pose estimation, image processing, image segmentation, knowledge distillation, and medical image processing. *The conference was held online 2021 due to the COVID-19 pandemic.
