Soumya Banerjee – författare

Machine Learning Models and Architectures for Biomedical Signal Processing presents the fundamental concepts of machine learning techniques for bioinformatics in an interactive way. The book investigates how efficient machine and deep learning models can support high-speed processors with reconfigurable architectures like graphic processing units (GPUs), Field programmable gate arrays (FPGAs), or any hybrid system. This great resource will be of interest to researchers working to increase the efficiency of hardware and architecture design for biomedical signal processing and signal processing techniques.- Covers the hardware architecture implementation of machine learning algorithms- Discusses the software implementation approach and the efficient hardware of machine learning application with FPGA- Presents the major design challenges and research potential in machine learning techniques

Machine Learning Models and Architectures for Biomedical Signal Processing presents the fundamental concepts of machine learning techniques for bioinformatics in an interactive way. The book investigates how efficient machine and deep learning models can support high-speed processors with reconfigurable architectures like graphic processing units (GPUs), Field programmable gate arrays (FPGAs), or any hybrid system. This great resource will be of interest to researchers working to increase the efficiency of hardware and architecture design for biomedical signal processing and signal processing techniques.Covers the hardware architecture implementation of machine learning algorithmsDiscusses the software implementation approach and the efficient hardware of machine learning application with FPGAPresents the major design challenges and research potential in machine learning techniques

This book constitutes the refereed post-proceedings of the 9th International Conference on Mobile, Secure, and Programmable Networking, MSPN 2023, held in  Paris, France, during October 26–27, 2023.The 15 full papers included in this book were carefully reviewed and selected from 31 submissions. They were organized in topical sections as follows vertical tools on machine leaning and artificial intelligence, network programming and Cloud computing, Industrial Internet of things, Digital Twins and Security.

This book constitutes the thoroughly refereed post-conference proceedings of the Third  International Conference on Mobile, Secure and Programmable Networking, held in Paris, France, in June 2017. The 17 papers presented in this volume were carefully reviewed and selected from 35 submissions. They discuss new trends in networking infrastructures, security, services and applications while focusing on virtualization and cloud computing, network programming, software defined networks (SDN) and their security.