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  • Automated Machine Learning for Person Re-Identification

    Series series Artificial Intelligence (R0)
    This book delves into the cutting-edge field of person re-identification (ReID), a critical area within deep learning and computer vision. Addressing key challenges in current ReID models, it presents novel research combining automated machine learning (AutoML) techniques across three core aspects: data augmentation, network architecture, and loss functions.Readers will discover five innovative ... Read more

    $125.99 USD

  • Graph Neural Network for Feature Extraction and Classification of Hyperspectral Remote Sensing Images

    Series series Intelligent Perception and Information Processing
    This book deals with hyperspectral image classification using graph neural network methods, focusing on classification model designing, graph information dissemination, and graph construction. In the book, various graph neural network based classifiers have been proposed for hyperspectral image classification to improve the classification accuracy. This book has promoted the application of graph ... Read more

    $143.99 USD

  • Graph Neural Network for Hyperspectral Image Clustering

    Series series Artificial Intelligence (R0)
    This book investigates detailed hyperspectral image clustering using graph neural network (graph learning) methods, focusing on the overall construction of the model, design of self-supervised methods, image pre-processing, and feature extraction of graph information. Multiple graph neural network-based clustering methods for hyperspectral images are proposed, effectively improving the clustering ... Read more

    $143.09 USD

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    Series series Computer Science (R0)
    This unique text/reference presents a comprehensive review of the state of the art in sparse representations, modeling and learning. The book examines both the theoretical foundations and details of algorithm implementation, highlighting the practical application of compressed sensing research in visual recognition and computer vision. Topics and features: describes sparse recovery approaches, ... Read more

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  • Latent Factor Analysis for High-dimensional and Sparse Matrices

    A particle swarm optimization-based approach

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    Series series Computer Science (R0)
    Latent factor analysis models are an effective type of machine learning model for addressing high-dimensional and sparse matrices, which are encountered in many big-data-related industrial applications. The performance of a latent factor analysis model relies heavily on appropriate hyper-parameters. However, most hyper-parameters are data-dependent, and using grid-search to tune these hyper ... Read more

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  • Self-Learning Optimal Control of Nonlinear Systems

    Adaptive Dynamic Programming Approach

    Series series Engineering (R0)
    This book presents a class of novel, self-learning, optimal control schemes based on adaptive dynamic programming techniques, which quantitatively obtain the optimal control schemes of the systems. It analyzes the properties identified by the programming methods, including the convergence of the iterative value functions and the stability of the system under iterative control laws, helping to ... Read more

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  • Pattern Recognition and Computer Vision

    7th Chinese Conference, PRCV 2024, Urumqi, China, October 18–20, 2024, Proceedings, Part XIII

    Series Book 13 - Springer Nature Proceedings Computer Science
    This 15-volume set LNCS 15031-15045 constitutes the refereed proceedings of the 7th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2024, held in Urumqi, China, during October 18–20, 2024.The 579 full papers presented were carefully reviewed and selected from 1526 submissions. The papers cover various topics in the broad areas of pattern recognition and computer vision, ... Read more

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  • Dynamical Behaviors of Fractional-Order Complex Dynamical Networks

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    This book benefits researchers, engineers, and graduate students in the field of fractional-order complex dynamical networks. Recently, the dynamical behaviors (e.g., passivity, finite-time passivity, synchronization, and finite-time synchronization, etc.) for fractional-order complex networks (FOCNs) have attracted considerable research attention in a wide range of fields, and a variety of ... Read more

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  • Normalization Techniques in Deep Learning

    by Lei Huang ...
    Series series eBColl Synthesis Collection 11
    This book presents and surveys normalization techniques with a deep analysis in training deep neural networks. In addition, the author provides technical details in designing new normalization methods and network architectures tailored to specific tasks. Normalization methods can improve the training stability, optimization efficiency, and generalization ability of deep neural networks (DNNs) and ... Read more

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  • Dynamic Network Representation Based on Latent Factorization of Tensors

    Series series Computer Science (R0)
    A dynamic network is frequently encountered in various real industrial applications, such as the Internet of Things. It is composed of numerous nodes and large-scale dynamic real-time interactions among them, where each node indicates a specified entity, each directed link indicates a real-time interaction, and the strength of an interaction can be quantified as the weight of a link. As the ... Read more

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  • Rough Sets

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    Series Book 2 - Springer Nature Proceedings Computer Science
    This three-volume set LNAI 15708-15709-15110 constitutes the proceedings of the International Joint Conference on Rough Sets, IJCRS 2025, held in Chongqing, China, during May 11–13, 2025.The 90 full papers included in these volumes were carefully reviewed and selected from 187 submissions. They are organized in topical sections as follows:Part I: Rough Set Models and Foundations; Fuzzy Rough Sets ... Read more

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  • Spatiotemporal Image Understanding

    Action, Activity and Behavior

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