IEEE Conference and Book Chapters : Title of the Book Reconfigurable Architecture Design and Computing Techniques for Deep Learning Algorithms Book Series: Sustainable Artificial Intelligence-Powered Applications Series ID: 17457

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Book Series:
Sustainable Artificial Intelligence-Powered Applications
Series ID: 17457

Implementation of digital signal processing applications using reconfigurable FPGA
Parallel computing in deep learning with FPGA
FPGA-based automatic speech emotion recognition using deep learning
Customizing FPGA for machine learning and deep learning applications
Low-power FPGA architectures for signal and image processing
Integrating FPGA technology into deep learning for signal processing tasks
FPGA-based deep learning for image processing applications
Enhancing machine learning using FPGA for signal processing
FPGA solutions for machine learning in image processing
Computational efficiency using FPGA-based deep neural networks
Parallel processing concepts using FPGA architectures
Fine-tuning algorithms for optimal FPGA performance
Hardware acceleration for machine and deep learning using FPGA
FPGA-based AI implementations for diverse image and signal processing applications
Hardware–software co-design for FPGA-based image and signal processing
FPGA design flow for machine learning and deep learning applications
Challenges in using FPGA for signal and image processing applications

Dr. Govindaraj V
Associate Professor, Department of ECE
KIT – CBE
Dr. S. Dhanasekar
Associate Professor, Department of ECE
Sri Eshwar College of Engineering, Coimbatore
Dr. K. Martin Sagayam
Associate Professor, Department of ECE
SRM Institute (TRP Engineering College), Trichy
Dr. Digvijay Pandey
Senior Lecturer, Department of Technical Education
Kanpur
Dr. Nguyen Ha Huy Cuong
Director, Software Development Centre
The University of Danang, Vietnam

📧 Email: reconfig25@gmail.com
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