{"product_id":"computer-vision-eccv-2022-17th-european-conference-tel-aviv-israel-october-2327-2022-proceedings-part-viii-9783031200731","title":"Computer Vision - ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23-27, 2022, Proceedings, Part VIII","description":"\u003cp\u003e\u003c\/p\u003e\u003cblockquote\u003eThe 39-volume set, consisting of the LNCS books 13661 to 13699, contains the refereed proceedings of the 17th European Conference on Computer Vision, ECCV 2022, held in Tel Aviv, Israel, during October 23–27, 2022. The papers cover various topics in computer vision, machine learning, deep neural networks, and more, with 1645 papers selected from 5804 submissions. \u003c\/blockquote\u003e\u003cp\u003e\u003cstrong\u003eFormat\u003c\/strong\u003e: Paperback \/ softback\u003cbr\u003e\u003cstrong\u003eLength\u003c\/strong\u003e: 751 pages\u003cbr\u003e\u003cstrong\u003ePublication date\u003c\/strong\u003e: 13 November 2022\u003cbr\u003e\u003cstrong\u003ePublisher\u003c\/strong\u003e: Springer International Publishing AG\u003cbr\u003e\u003c\/p\u003e \u003cp\u003eThe 39-volume set, comprising the LNCS books 13661 until 13699, represents the refereed proceedings of the 17th European Conference on Computer Vision (ECCV 2022), held in Tel Aviv, Israel, from October 23 to 27, 2022. A total of 1645 papers were presented in these proceedings, following a rigorous review process from a pool of 5804 submissions. These papers cover a wide range of topics within the field of computer vision, including:\u003cbr\u003e\u003cbr\u003eComputer Vision: This encompasses the study and application of techniques for acquiring, processing, analyzing, and understanding visual data from images and videos. It involves tasks such as object detection, recognition, tracking, and scene understanding.\u003cbr\u003e\u003cbr\u003eMachine Learning: Machine learning is a branch of computer science that focuses on teaching computers to learn from data and make predictions or decisions based on that learning. It involves techniques such as supervised learning, unsupervised learning, and reinforcement learning.\u003cbr\u003e\u003cbr\u003eDeep Neural Networks: Deep neural networks are a type of neural network architecture that uses multiple layers of interconnected neurons to model and understand complex patterns in data. They have been widely used in areas such as image recognition, speech recognition, and natural language processing.\u003cbr\u003e\u003cbr\u003eReinforcement Learning: Reinforcement learning is a type of machine learning that involves an agent learning to interact with an environment by receiving rewards or penalties for its actions. It is used in autonomous systems, such as self-driving cars, and game playing.\u003cbr\u003e\u003cbr\u003eObject Recognition: Object recognition is the process of identifying and categorizing objects in images or videos. It involves techniques such as feature extraction, classification, and tracking.\u003cbr\u003e\u003cbr\u003eImage Classification: Image classification is the process of assigning a label to an image based on its content. It involves techniques such as convolutional neural networks, decision trees, and support vector machines.\u003cbr\u003e\u003cbr\u003eImage Processing: Image processing is the manipulation and analysis of digital images to enhance their appearance, remove noise, or extract features. It involves techniques such as image enhancement, filtering, and segmentation.\u003cbr\u003e\u003cbr\u003eObject Detection: Object detection is the process of identifying and locating objects in images or videos. It involves techniques such as convolutional neural networks, bounding boxes, and region-based methods.\u003cbr\u003e\u003cbr\u003eSemantic Segmentation: Semantic segmentation is the process of dividing an image into different regions based on its semantic content, such as objects, backgrounds, or foreground. It involves techniques such as convolutional neural networks and deep learning.\u003cbr\u003e\u003cbr\u003eHuman Pose Estimation: Human pose estimation is the process of determining the position and orientation of the body parts of a human in an image or video. It involves techniques such as deep learning and computer vision.\u003cbr\u003e\u003cbr\u003eThree-Dimensional Reconstruction: Three-dimensional reconstruction is the process of creating a three-dimensional model of an object or scene from multiple two-dimensional images or videos. It involves techniques such as photogrammetry and 3D modeling.\u003cbr\u003e\u003cbr\u003eStereo Vision: Stereo vision is the process of obtaining depth information from images or videos using two or more cameras. It involves techniques such as disparity estimation and stereo matching.\u003cbr\u003e\u003cbr\u003eComputational Photography: Computational photography is the use of computer algorithms to enhance or modify images or videos. It involves techniques such as image optimization, color correction, and image synthesis.\u003cbr\u003e\u003cbr\u003eNeural Networks: Neural networks are a type of artificial intelligence that mimics the behavior of the human brain. They are used in a wide range of applications, including image recognition, speech recognition, and natural language processing.\u003cbr\u003e\u003cbr\u003eImage Coding: Image coding is the process of compressing digital images to reduce their size without losing quality. It involves techniques such as JPEG compression, PNG compression, and lossless compression.\u003cbr\u003e\u003cbr\u003eImage Reconstruction: Image reconstruction is the process of restoring an image from a set of corrupted or incomplete data. It involves techniques such as interpolation, denoising, and reconstruction algorithms.\u003cbr\u003e\u003cbr\u003eObject Recognition: Object recognition is the process of identifying and categorizing objects in images or videos. It involves techniques such as feature extraction, classification, and tracking.\u003cbr\u003e\u003cbr\u003eMotion Estimation: Motion estimation is the process of estimating the motion of objects in images or videos. It involves techniques such as optical flow, motion tracking, and particle filters.\u003cbr\u003e\u003cbr\u003eThe 17th European Conference on Computer Vision (ECCV 2022) was a highly esteemed event that brought together experts and researchers from around the world to discuss the latest advancements in computer vision and related fields. The conference featured a wide range of presentations, including keynote speeches, oral presentations, and poster sessions, covering a diverse set of topics.\u003cbr\u003e\u003cbr\u003eOne of the key highlights of ECCV 2022 was the quality of the research presented. The conference received a total of 5804 submissions, from which 1645 papers were selected for presentation. The papers covered a wide range of topics, including 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, and more.\u003cbr\u003e\u003cbr\u003eThe conference also featured several workshops and tutorials, providing opportunities for researchers to learn about new techniques and tools in the field. The workshops were led by experts in the field and covered topics such as deep learning, computer vision, and machine learning, among others.\u003cbr\u003e\u003cbr\u003eIn conclusion, the 17th European Conference on Computer Vision (ECCV 2022) was a successful event that showcased the latest advancements in computer vision and related fields. The conference featured a wide range of presentations, workshops, and tutorials, providing opportunities for researchers to learn about new techniques and tools. The quality of the research presented was impressive, and the conference played a significant role in advancing the field of computer vision.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWeight\u003c\/strong\u003e: 1223g\u003cbr\u003e\u003cstrong\u003eDimension\u003c\/strong\u003e: 235 x 155 (mm)\u003cbr\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e: 9783031200731\u003cbr\u003e \u003cstrong\u003eEdition number\u003c\/strong\u003e: 1st ed. 2022\u003c\/p\u003e","brand":"Shulph Ink","offers":[{"title":"Paperback \/ softback","offer_id":45290377249018,"sku":"9783031200731","price":85.39,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0522\/4297\/2845\/products\/noImage_1_774b38b3-59cf-4abd-868a-b92c324b8041.jpg?v=1706343358","url":"https:\/\/shulphink.com\/products\/computer-vision-eccv-2022-17th-european-conference-tel-aviv-israel-october-2327-2022-proceedings-part-viii-9783031200731","provider":"Shulph Ink","version":"1.0","type":"link"}