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Document Analysis and Recognition - ICDAR 2023
This six-volume set of LNCS 14187, 14188, 14189, 14190, 14191 and 14192 constitutes the refereed proceedings of the 17th International Conference on Document Analysis and Recognition, ICDAR 2021, held in San José, CA, USA, in August 2023. The 53 full papers were carefully reviewed and selected from 316 submissions, and are presented with 101 poster presentations. The papers are organized into the following topical sections: Graphics Recognition, Frontiers in Handwriting Recognition, Document Analysis and Recognition.
Computer Vision – ACCV 2022
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.
Natural Methane Emissions in a Changing Arctic - Implications for Climate and Environment
Natural emissions of methane have received much attention over the last decade due to the documented increase of methane in the atmosphere and high global warming potential relative to CO2. Over the past few decades the Arctic has been warming approximately four times faster than the rest of the planet, driving a pressing need to assess the current and future vulnerability of various natural methane sources. In the Arctic, vast amounts of methane is stored in soils and permafrost or is being generated as permafrost thaw continues. Additionally, there are large stores of methane in Arctic gas hydrates, a solid form of concentrated methane and water, and in numerous settings, including deep-water marine areas, on continental shelves hosting relict subsea permafrost and gas hydrate, in and beneath onshore permafrost, and likely beneath the Greenland Ice Sheet. Continued climate warming is making methane leakage more likely. Even deeper conventional gas reservoirs could leak methane as the overlying permafrost degrades.
Advanced Methods and Deep Learning in Computer Vision
Advanced Methods and Deep Learning in Computer Vision presents advanced computer vision methods, emphasizing machine and deep learning techniques that have emerged during the past 5–10 years. The book provides clear explanations of principles and algorithms supported with applications. Topics covered include machine learning, deep learning networks, generative adversarial networks, deep reinforcement learning, self-supervised learning, extraction of robust features, object detection, semantic segmentation, linguistic descriptions of images, visual search, visual tracking, 3D shape retrieval, image inpainting, novelty and anomaly detection. This book provides easy learning for researchers and practitioners of advanced computer vision methods, but it is also suitable as a textbook for a second course on computer vision and deep learning for advanced undergraduates and graduate students. - Provides an important reference on deep learning and advanced computer methods that was created by leaders in the field - Illustrates principles with modern, real-world applications - Suitable for self-learning or as a text for graduate courses
