Crowd Assisted Networking And Computing
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Crowd Assisted Networking and Computing
Crowd computing, crowdsourcing, crowd-associated network (CrAN), crowd-assisted sensing are some examples of crowd-based concepts that harness the power of people on the web or connected via web-like infrastructure to do tasks that are often difficult for individual users or computers to do alone. This creates many challenging issues like assessing reliability and correctness of crowd generated information, delivery of data and information via crowd, middleware for supporting crowdsourcing and crowd computing tasks, crowd associated networking and its security, Quality of Information (QoI) issues, etc. This book compiles the latest advances in the relevant fields.
Crowd Assisted Networking and Computing
Crowd computing, crowdsourcing, crowd-associated network (CrAN), crowd-assisted sensing are some examples of crowd-based concepts that harness the power of people on the web or connected via web-like infrastructure to do tasks that are often difficult for individual users or computers to do alone. This creates many challenging issues like assessing reliability and correctness of crowd generated information, delivery of data and information via crowd, middleware for supporting crowdsourcing and crowd computing tasks, crowd associated networking and its security, Quality of Information (QoI) issues, etc. This book compiles the latest advances in the relevant fields.
Intelligent Image and Video Analytics
Video has rich information including meta-data, visual, audio, spatial and temporal data which can be analysed to extract a variety of low and high-level features to build predictive computational models using machine-learning algorithms to discover interesting patterns, concepts, relations, and associations. This book includes a review of essential topics and discussion of emerging methods and potential applications of video data mining and analytics. It integrates areas like intelligent systems, data mining and knowledge discovery, big data analytics, machine learning, neural network, and deep learning with focus on multimodality video analytics and recent advances in research/applications. Features: Provides up-to-date coverage of the state-of-the-art techniques in intelligent video analytics. Explores important applications that require techniques from both artificial intelligence and computer vision. Describes multimodality video analytics for different applications. Examines issues related to multimodality data fusion and highlights research challenges. Integrates various techniques from video processing, data mining and machine learning which has many emerging indoors and outdoors applications of smart cameras in smart environments, smart homes, and smart cities. This book aims at researchers, professionals and graduate students in image processing, video analytics, computer science and engineering, signal processing, machine learning, and electrical engineering.