| 書目名稱 | Neural Networks with Model Compression | | 編輯 | Baochang Zhang,Tiancheng Wang,David Doermann | | 視頻video | http://file.papertrans.cn/664/663727/663727.mp4 | | 概述 | Review recent advances in CNN compression and acceleration.Elaborate recent advances on deep model compression technologies.Introduce applications of model compression in image classification, speech | | 叢書名稱 | Computational Intelligence Methods and Applications | | 圖書封面 |  | | 描述 | .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 floating-point 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, our book will focus on CNN compression and acceleration, which are important for the research community. We will describe numerous methods, including parameter quantization, network pruning, low-rank decomposition and knowledge distillation. More recently, to reduce the burden of handcrafted architecture design, neural architecture search (NAS) has been used to automatically build neural networks by searching over a vast architecture space. Our book will also introduce NAS due to its superiority and state-of-the-art performance in various applications, such as image classification and object detection. We also describe extensive applications of compressed deep models on image classification, speech rec | | 出版日期 | Book 2024 | | 關(guān)鍵詞 | Binary Neural Network; Model Compression; Artificial Intelligence; Machine Learning; Computer Vision | | 版次 | 1 | | doi | https://doi.org/10.1007/978-981-99-5068-3 | | isbn_softcover | 978-981-99-5070-6 | | isbn_ebook | 978-981-99-5068-3Series ISSN 2510-1765 Series E-ISSN 2510-1773 | | issn_series | 2510-1765 | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor |
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