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Translating Chinese in Malaysia
Shedding light on the nuances of cross-cultural communication, this edited volume offers insights into how Chinese Malaysians, a major ethnic group, navigate the complexities of translating across diverse languages. This book unveils the unique landscape of translation from Chinese in Malaysia, where the emphasis lies not just in theoretical nuances but in the practical application of bridging linguistic divides. The narrative unfolds the dedicated efforts of the local Chinese community, passionately engaged in translating literary gems and unraveling language intricacies. It provides a platform to explore how Chinese Malaysians use translation as a tool to maintain and transmit their lingui...
Computer Vision – ECCV 2020
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.
Proceedings of the Sixth International Conference on Computer Supported Cooperative Work in Design
Computer-supported co-operative work (CSCW) is a research area that aims at integrating the works of several people involved in a common goal, inside a co-operative universe, through the sharing of resources in an efficient way. This report contains the papers presented at a conference on CSCW in design. Topics covered include: techniques, methods, and tools for CSCW in design; social organization of the CSCW process; integration of methods & tools within the work organization; co-operation in virtual enterprises and electronic businesses; CSCW in design & manufacturing; interaction between the CSCW approach and knowledge reuse as found in knowledge management; intelligent agent & multi-agent systems; Internet/World Wide Web and CSCW in design; and applications & test beds.
Medical Image Computing and Computer Assisted Intervention – MICCAI 2021
The eight-volume set LNCS 12901, 12902, 12903, 12904, 12905, 12906, 12907, and 12908 constitutes the refereed proceedings of the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021, held in Strasbourg, France, in September/October 2021.* The 531 revised full papers presented were carefully reviewed and selected from 1630 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: image segmentation Part II: machine learning - self-supervised learning; machine learning - semi-supervised learning; and machine learning - weakly supervised learning Part III: machine learning - advances in m...
Computer Supported Cooperative Work and Social Computing
This book constitutes the refereed proceedings of the 14th CCF Conference on Computer Supported Cooperative Work and Social Computing, ChineseCSCW 2019, held in Kunming, China, in August 2019. The 52 revised full papers and 10 short papers were carefully reviewed and selected from 169 submissions. The papers of this volume are organized in topical sections on: collaborative models, approaches, algorithms, and systems; social computing (online communities, crowdsourcing, recommendation, sentiment analysis, etc.); AI for CSCW and social computing.
Human Centered Computing
This book constitutes revised selected papers from the refereed proceedings of the First Human Centered Computing Conference, HCC 2014, that consolidated and further develops the successful ICPCA/SWS conferences on Pervasive Computing and the Networked World. The 54 full papers and 30 short papers presented in this volume were carefully reviewed and selected from 152 submissions. These proceedings present research papers investigating into a variety of aspects towards human centric intelligent societies. They cover the categories: infrastructure and devices; service and solution; data and knowledge; and community.
Cooperative Design, Visualization, and Engineering
This book constitutes the refereed proceedings of the Second International Conference on Cooperative Design, Visualization, and Engineering, CDVE 2005, held in Palma de Mallorca, Spain, in September 2005. The 28 revised full papers presented were carefully reviewed and selected from over 100 submissions. The papers cover all current issues in cooperative design, visualization, engineering, and other cooperative applications. Topics addressed are such as constraint maintenance, decision support, and security enforcement for CDVE. Case studies and application specific developments are among the cooperative visualization papers. Along the line of cooperative engineering, knowledge management, reconfigurability, and concurrency control are major issues addressed.
Binary Neural Networks
Deep learning has achieved impressive results in image classification, computer vision, and natural language processing. To achieve better performance, deeper and wider networks have been designed, which increase the demand for computational resources. The number of floatingpoint operations (FLOPs) has increased dramatically with larger networks, and this has become an obstacle for convolutional neural networks (CNNs) being developed for mobile and embedded devices. In this context, Binary Neural Networks: Algorithms, Architectures, and Applications will focus on CNN compression and acceleration, which are important for the research community. We will describe numerous methods, including par...
Visual Domain Adaptation in the Deep Learning Era
Solving problems with deep neural networks typically relies on massive amounts of labeled training data to achieve high performance. While in many situations huge volumes of unlabeled data can be and often are generated and available, the cost of acquiring data labels remains high. Transfer learning (TL), and in particular domain adaptation (DA), has emerged as an effective solution to overcome the burden of annotation, exploiting the unlabeled data available from the target domain together with labeled data or pre-trained models from similar, yet different source domains. The aim of this book is to provide an overview of such DA/TL methods applied to computer vision, a field whose popularit...
