1# Library to Find Best eBook for Read
Author : Muhammad Arsalan
Release :
Genre :
Kind : eBook
Book Rating : 184/5 ( reviews)
Book Synopsis Optimization of Spiking Neural Networks for Radar Applications by : Muhammad Arsalan
Download or read book Optimization of Spiking Neural Networks for Radar Applications written by Muhammad Arsalan. This book was released on . Available in PDF, EPUB and Kindle. Book excerpt:
Author : Muhammad Arsalan
Release : 2024-09-26
Genre : Computers
Kind : eBook
Book Rating : 176/5 ( reviews)
Book Synopsis Optimization of Spiking Neural Networks for Radar Applications by : Muhammad Arsalan
Download or read book Optimization of Spiking Neural Networks for Radar Applications written by Muhammad Arsalan. This book was released on 2024-09-26. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a comprehensive exploration of the transformative role that edge devices play in advancing Internet of Things (IoT) applications. By providing real-time processing, reduced latency, increased efficiency, improved security, and scalability, edge devices are at the forefront of enabling IoT growth and success. As the adoption of AI on the edge continues to surge, the demand for real-time data processing is escalating, driving innovation in AI and fostering the development of cutting-edge applications and use cases. Delving into the intricacies of traditional deep neural network (deepNet) approaches, the book addresses concerns about their energy efficiency during inference, particularly for edge devices. The energy consumption of deepNets, largely attributed to Multiply-accumulate (MAC) operations between layers, is scrutinized. Researchers are actively working on reducing energy consumption through strategies such as tiny networks, pruning approaches, and weight quantization. Additionally, the book sheds light on the challenges posed by the physical size of AI accelerators for edge devices. The central focus of the book is an in-depth examination of SNNs' capabilities in radar data processing, featuring the development of optimized algorithms.
Author : Colton C. Smith
Release : 2021
Genre : Deep learning (Machine learning)
Kind : eBook
Book Rating : /5 ( reviews)
Book Synopsis The Evaluation of Current Spiking Neural Network Conversion Methods in Radar Data by : Colton C. Smith
Download or read book The Evaluation of Current Spiking Neural Network Conversion Methods in Radar Data written by Colton C. Smith. This book was released on 2021. Available in PDF, EPUB and Kindle. Book excerpt: The continued growth and application of deep learning has resulted in a vast increase in energy and computational requirements. Biologically inspired spiking neural networks (SNNs) and neuromorphic hardware pose one possible solution to this issue. Optimization of these methods, however, remains difficult and less effective compared with that of traditional artificial neural networks (ANNs). A number of methods have been recently proposed to optimize SNNs through the conversion of architecturally equivalent ANNs. However, most benchmarking of these methods has only been done separately through experiments in the respective papers. Therefore, the performance of the solutions is inevitably biased due to the differences in levels and goals of optimization. Moreover, certain papers also relied heavily on architectural improvements to the base ANN which can be separated from the actual method of conversion [1] [2]. In this thesis, we thoroughly evaluate and compare the performance of the major ANN-to SNN conversion solutions based on a new set of performance metrics we proposed. Additionally, we implement expansions to certain methods, allowing for more comprehensive and fair comparisons. Furthermore, the hyperparameters of each method are optimized uniformly to reduce biases towards specific methods. Our implementations and comparisons of SNN solutions are carried out on one-dimensional radar data. To the best of our knowledge, this is the first such effort in the domain of radar applications.
Author : Avik Santra
Release : 2020-09-30
Genre : Technology & Engineering
Kind : eBook
Book Rating : 473/5 ( reviews)
Book Synopsis Deep Learning Applications of Short-Range Radars by : Avik Santra
Download or read book Deep Learning Applications of Short-Range Radars written by Avik Santra. This book was released on 2020-09-30. Available in PDF, EPUB and Kindle. Book excerpt: This exciting new resource covers various emerging applications of short range radars, including people counting and tracking, gesture sensing, human activity recognition, air-drawing, material classification, object classification, vital sensing by extracting features such as range-Doppler Images (RDI), range-cross range images, Doppler Spectrogram or directly feeding raw ADC data to the classifiers. The book also presents how deep learning architectures are replacing conventional radar signal processing pipelines enabling new applications and results. It describes how deep convolutional neural networks (DCNN), long-short term memory (LSTM), feedforward networks, regularization, optimization algorithms, connectionist This exciting new resource presents emerging applications of artificial intelligence and deep learning in short-range radar. The book covers applications ranging from industrial, consumer space to emerging automotive applications. The book presents several human-machine interface (HMI) applications, such as gesture recognition and sensing, human activity classification, air-writing, material classification, vital sensing, people sensing, people counting, people localization and in-cabin automotive occupancy and smart trunk opening. The underpinnings of deep learning are explored, outlining the history of neural networks and the optimization algorithms to train them. Modern deep convolutional neural network (DCNN), popular DCNN architectures for computer vision and their features are also introduced. The book presents other deep learning architectures, such as long-short term memory (LSTM), auto-encoders, variational auto-encoders (VAE), and generative adversarial networks (GAN). The application of human activity recognition as well as the application of air-writing using a network of short-range radars are outlined. This book demonstrates and highlights how deep learning is enabling several advanced industrial, consumer and in-cabin applications of short-range radars, which weren't otherwise possible. It illustrates various advanced applications, their respective challenges, and how they are been addressed using different deep learning architectures and algorithms.
Author : Sevgi Zubeyde Gurbuz
Release : 2020-12-31
Genre : Technology & Engineering
Kind : eBook
Book Rating : 520/5 ( reviews)
Book Synopsis Deep Neural Network Design for Radar Applications by : Sevgi Zubeyde Gurbuz
Download or read book Deep Neural Network Design for Radar Applications written by Sevgi Zubeyde Gurbuz. This book was released on 2020-12-31. Available in PDF, EPUB and Kindle. Book excerpt: Novel deep learning approaches are achieving state-of-the-art accuracy in the area of radar target recognition, enabling applications beyond the scope of human-level performance. This book provides an introduction to the unique aspects of machine learning for radar signal processing that any scientist or engineer seeking to apply these technologies ought to be aware of.
