This volume comprises the select proceedings of the 3rd International Conference on Signal & Data Processing - ICSDP 2023. The contents focus on the latest research and developments in the field of artificial intelligence & machine learning, Internet of Things (IoT), cybernetics, advanced communication systems, VLSI embedded systems, power electronics and automation, MEMS/ nanotechnology, renewable energy, bioinformatics, data acquisition and mining, antenna & RF systems, power systems, biomedical engineering, aerospace & navigation. This volume will prove to be a valuable resource for those in academia and industry.…mehr
This volume comprises the select proceedings of the 3rd International Conference on Signal & Data Processing - ICSDP 2023. The contents focus on the latest research and developments in the field of artificial intelligence & machine learning, Internet of Things (IoT), cybernetics, advanced communication systems, VLSI embedded systems, power electronics and automation, MEMS/ nanotechnology, renewable energy, bioinformatics, data acquisition and mining, antenna & RF systems, power systems, biomedical engineering, aerospace & navigation. This volume will prove to be a valuable resource for those in academia and industry.
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Autorenporträt
Raghunath Shevgaonkar has worked in higher education in India for more than three decades. Currently, he serves as the Vice Chancellor of Bennett University, Noida, India. Previously, as the Vice Chancellor of the University of Pune and the Director of IIT Delhi, he focused on bringing about systemic reforms and changes. He has also been a Faculty Research Associate with the University of Maryland, US, and a Visiting Professor at the University of Nebraska-Lincoln, US, ETH Zurich, and ISEP Paris. During his time at IIT Bombay, he played a significant role in establishing the Centre for Distance Engineering Education. Additionally, he was instrumental in commissioning one of the world's largest Decameter Wave Telescopes at the Indian Institute of Astrophysics and Raman Research Institute, Bangalore. His teaching and research areas include strategic planning, optical communication, image processing, and computational electromagnetics. Prof. Shevgaonkar has been honored with several awards, including the IEEE Undergraduate Teaching Award (2011), Headline Today's Education Leadership Award (2012), and the Devang Mehta Business School Award (2010). Wing Commander (Dr.) Debashis Adhikari (Retired) holds a B.Tech. from the Institute of Radio Physics & Electronics, Calcutta University, an M.E. from Pune University, and a Ph.D. in Wireless Communication from the Defence Institute of Advanced Technology (DRDO), Pune. He served the Indian Air Force for 23 years, reaching the rank of Wing Commander before his premature separation. Dr. Adhikari has extensive experience in surface-to-air missile systems and wireless systems of the IAF and has been involved in various indigenization and modification projects. He has delivered guest lectures at various Defense PSUs, several DRDO labs, and the Indian Navy on Missile Guidance. With a total experience of 31 years, Dr. Adhikari has had faculty tenures at DIAT (DRDO) Pune, Symbiosis Institute of Technology, Pune, and was previously a Professor & Dean at the School of Electrical Engineering at MIT AOE, Pune, before joining VIT Bhopal. His area of interest is MIMO wireless systems, and he is currently serving as the Dean of the School of Electrical & Electronics Engineering at VIT Bhopal University, as well as the Dean of Faculty Affairs of the University. Soumitra Keshari Nayak holds a Doctorate in Sensor Systems & Signal Processing from IIT Bombay. He has graduated with an M.Tech. from the Dept. of Instrumentation & Electronics (IEE), Jadavpur University, Kolkata, and a B.Tech. in Applied Electronics & Instrumentation (AEIE) from Biju Patnaik University of Technology (BPUT), Odisha. Currently, he is working as an Assistant Professor at VIT Bhopal University and Program Chair of B.Tech ECE(AI & Cybernetics). With a keen interest in robotics (navigation and path planning), he has been actively involved in improving the laboratory and research facilities for students and faculty in autonomous systems, embedded & IoT. He is a member of the IEEE Robotics and Signal Processing Society and has participated in several lectures and activities at IEEE societies. His research interests include Sensor Systems, Statistical Signal Processing, Robotics, Smart IoT, and Embedded System Design. Febe de Wet is a member of the Conversational AI team at BMW South Africa's IT Hub. She is also an extraordinary associate professor at Stellenbosch University's Department of Electrical and Electronic Engineering. Her research interests include statistical pattern recognition, speech resource development, and automatic speech recognition. She is especially interested in developing language technology for South Africa's indigenous languages and in educational applications of speech technology.
Inhaltsangabe
Data Acquisition and Pre Processing of EEG signals using Brainwave sensor. Comparison of Algorithms For Efficient Skin Cancer Classification Using Deep Neural Networks. Performance Analysis of Optical Networks Using Deep Reinforcement Learning. Performance Analysis of Optical Networks Using Deep Reinforcement Learning. Exploring deep learning models for classifying wind profiler Doppler power spectrum contaminated by ground clutter. Efficient Rice Yield Classification: Accelerating ANN Processing on PYNQ Z2 Processor. FPGA Based Implementation of Cuffless Blood Pressure Measurement Using Photoplethysmogram Signal. Classification of Currencies as Authentic or Counterfeit: A Data Driven Approach. Classification of Currencies as Authentic or Counterfeit: A Data Driven Approach. Suppression of Electro Magnetic Emission in Electric Vehicle for EMC. Suppression of Electro Magnetic Emission in Electric Vehicle for EMC. Machine Learning Model based on Deep Neural Networks for Emotion Detection using Audio Visual Modalities. Enhancing the Leaf Disease Detection through Convolutional Neural Network. Gaussian Processes for Automating Model Selection. NAS for Automated ML Deployment on Extreme Edge Devices. Unlocking Personality Insights: Assessing Videos with Deep Learning Techniques. Alertness Detection From Video Using Saccadic Velocity Profile. Management of Power and Power Quality in Micro grid using Adaptive Controller. Material Selection and Performance Analysis of Organic MEMS Cantilever Force Sensors with Integrated Piezoresistive Readout. Management of Power and Power Quality in Micro grid using Adaptive Controller. Material Selection and Performance Analysis of Organic MEMS Cantilever Force Sensors with Integrated Piezoresistive Readout. Utilizing Convolutional Neural Networks and Mel Spectrograms for Indian Spoken Language Detection.
Data Acquisition and Pre Processing of EEG signals using Brainwave sensor. Comparison of Algorithms For Efficient Skin Cancer Classification Using Deep Neural Networks. Performance Analysis of Optical Networks Using Deep Reinforcement Learning. Performance Analysis of Optical Networks Using Deep Reinforcement Learning. Exploring deep learning models for classifying wind profiler Doppler power spectrum contaminated by ground clutter. Efficient Rice Yield Classification: Accelerating ANN Processing on PYNQ Z2 Processor. FPGA Based Implementation of Cuffless Blood Pressure Measurement Using Photoplethysmogram Signal. Classification of Currencies as Authentic or Counterfeit: A Data Driven Approach. Classification of Currencies as Authentic or Counterfeit: A Data Driven Approach. Suppression of Electro Magnetic Emission in Electric Vehicle for EMC. Suppression of Electro Magnetic Emission in Electric Vehicle for EMC. Machine Learning Model based on Deep Neural Networks for Emotion Detection using Audio Visual Modalities. Enhancing the Leaf Disease Detection through Convolutional Neural Network. Gaussian Processes for Automating Model Selection. NAS for Automated ML Deployment on Extreme Edge Devices. Unlocking Personality Insights: Assessing Videos with Deep Learning Techniques. Alertness Detection From Video Using Saccadic Velocity Profile. Management of Power and Power Quality in Micro grid using Adaptive Controller. Material Selection and Performance Analysis of Organic MEMS Cantilever Force Sensors with Integrated Piezoresistive Readout. Management of Power and Power Quality in Micro grid using Adaptive Controller. Material Selection and Performance Analysis of Organic MEMS Cantilever Force Sensors with Integrated Piezoresistive Readout. Utilizing Convolutional Neural Networks and Mel Spectrograms for Indian Spoken Language Detection.
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