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Titlebook: Computing and Machine Learning; Proceedings of CML 2 Jagdish Chand Bansal,Samarjeet Borah,Said Salhi Conference proceedings 2024 The Editor

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書目名稱Computing and Machine Learning
副標題Proceedings of CML 2
編輯Jagdish Chand Bansal,Samarjeet Borah,Said Salhi
視頻videohttp://file.papertrans.cn/243/242369/242369.mp4
概述Presents recent research in computing and machine learning.Discusses the outcomes of CML 2024, held in Sikkim, India, during March 2024.Serves as a reference resource for researchers and practitioners
叢書名稱Lecture Notes in Networks and Systems
圖書封面Titlebook: Computing and Machine Learning; Proceedings of CML 2 Jagdish Chand Bansal,Samarjeet Borah,Said Salhi Conference proceedings 2024 The Editor
描述.This book features high-quality research papers presented at the International Conference on Computing and Machine Learning (CML 2024), organized by the Department of Computer Applications, Sikkim Manipal Institute of Technology, Sikkim Manipal?University, Sikkim, India during April 29–30, 2024. The book presents diverse range of topics, including machine learning algorithms and models, deep learning and neural networks, computer vision and image processing, natural language processing, robotics and automation, reinforcement learning, big data analytics, cloud computing, Internet of things, human–robot interaction, ethical and social implications of AI, applications in healthcare, finance, and industry, computer modeling, quantum computing, high-performance computing, cognitive and parallel?computing, cloud computing, distributed computing, embedded computing, human-centered computing, and mobile computing..
出版日期Conference proceedings 2024
關鍵詞Deep learning; Big data analytics; Natural language processing; Cognitive computing; Artificial intellig
版次1
doihttps://doi.org/10.1007/978-981-97-6588-1
isbn_softcover978-981-97-6587-4
isbn_ebook978-981-97-6588-1Series ISSN 2367-3370 Series E-ISSN 2367-3389
issn_series 2367-3370
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
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Optimizing the U-Net Model for Segmenting the Lung Opacity Regions in Chest Radiographs,and appropriate treatment. To ensure continuous neuron activity during the training process, the ReLU activation in the U-Net model is replaced with the Leaky ReLU activation. The optimized U-Net model is trained and validated using 90 labeled lung opacity chest radiographs. U-Net‘s adaptability to
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Intelligent Surveillance Camera System Based on Object Tracking,del is used to implement and develop the proposed system. This model is one of the most advanced human object detection models and has very high accuracy with an mAP50 value of 0.878. Besides, the Deep SORT model is used for object tracking. Then, the system checks whether the detected object is in
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Enhancing Efficiency and Functionality of Voice-Controlled Cars Through NLP Techniques and Additionnd obstacle recognition using an ultrasonic sensor to increase its usefulness in real-world scenarios. Performance study uses Python and data visualization tools to visualize the relationship between execution time and the number of instructions, which offers valuable insights for future voice-contr
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