Biology-Inspired Engineering and Engineering-Inspired Biology

Biology-Inspired Engineering and Engineering-Inspired Biology PDF Author: Jan-Matthias Braun
Publisher: Frontiers Media SA
ISBN: 288966340X
Category : Science
Languages : en
Pages : 165

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Book Description

Biology-Inspired Engineering and Engineering-Inspired Biology

Biology-Inspired Engineering and Engineering-Inspired Biology PDF Author: Jan-Matthias Braun
Publisher: Frontiers Media SA
ISBN: 288966340X
Category : Science
Languages : en
Pages : 165

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Book Description


Bio-inspired Audio Processing, Models and Systems

Bio-inspired Audio Processing, Models and Systems PDF Author: Shih-Chii Liu
Publisher: Frontiers Media SA
ISBN: 2889632326
Category :
Languages : en
Pages : 200

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Book Description
Neurophysiology and biology provide useful starting points to help us understand and build better audio processing systems. The papers in this special issue address hardware implementations, spiking networks, sound identification, and attention decoding.

Neuromorphic Engineering Systems and Applications

Neuromorphic Engineering Systems and Applications PDF Author: Chiara Bartolozzi
Publisher: Frontiers Media SA
ISBN: 2889717232
Category : Science
Languages : en
Pages : 198

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Understanding and Bridging the Gap between Neuromorphic Computing and Machine Learning

Understanding and Bridging the Gap between Neuromorphic Computing and Machine Learning PDF Author: Lei Deng
Publisher: Frontiers Media SA
ISBN: 2889667421
Category : Science
Languages : en
Pages : 200

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Book Description


Investigations in Pattern Recognition and Computer Vision for Industry 4.0

Investigations in Pattern Recognition and Computer Vision for Industry 4.0 PDF Author: Chowdhary, Chiranji Lal
Publisher: IGI Global
ISBN: 1668486032
Category : Computers
Languages : en
Pages : 293

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Book Description
The approaches to computer vision have undergone a long journey in recent years, but still, innovations are continuing with leverage increases in computing power, new data availability, and new ways to leverage machine-learning algorithms. As a branch of artificial intelligence (AI), computer vision brings meaningful information from images and videos. Such innovations help communicators to run better campaigns, amplify messages further, and stand out in a noisy, crowded marketplace. Investigations in Pattern Recognition and Computer Vision for Industry 4.0 provides a holistic discussion of the new practical applications and use cases of computer vision and communications. Covering topics such as social media filters, mobile computer vision, and AI-powered image editing, this book is ideal for academicians, researchers, postgraduate students, professional data analysts, research and development centers, organizations dealing with healthcare informatics, and IT firms.

Understanding and Bridging the Gap between Neuromorphic Computing and Machine Learning, volume II

Understanding and Bridging the Gap between Neuromorphic Computing and Machine Learning, volume II PDF Author: Huajin Tang
Publisher: Frontiers Media SA
ISBN: 283255363X
Category : Science
Languages : en
Pages : 152

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Book Description
Towards the long-standing dream of artificial intelligence, two solution paths have been paved: (i) neuroscience-driven neuromorphic computing; (ii) computer science-driven machine learning. The former targets at harnessing neuroscience to obtain insights for brain-like processing, by studying the detailed implementation of neural dynamics, circuits, coding and learning. Although our understanding of how the brain works is still very limited, this bio-plausible way offers an appealing promise for future general intelligence. In contrast, the latter aims at solving practical tasks typically formulated as a cost function with high accuracy, by eschewing most neuroscience details in favor of brute force optimization and feeding a large volume of data. With the help of big data (e.g. ImageNet), high-performance processors (e.g. GPU, TPU), effective training algorithms (e.g. artificial neural networks with gradient descent training), and easy-to-use design tools (e.g. Pytorch, Tensorflow), machine learning has achieved superior performance in a broad spectrum of scenarios. Although acclaimed for the biological plausibility and the low power advantage (benefit from the spike signals and event-driven processing), there are ongoing debates and skepticisms about neuromorphic computing since it usually performs worse than machine learning in practical tasks especially in terms of the accuracy.

Bio-inspired computation and its applications

Bio-inspired computation and its applications PDF Author: Tinggui Chen
Publisher: Frontiers Media SA
ISBN: 2832527833
Category : Science
Languages : en
Pages : 939

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Book Description


Towards Neuromorphic Machine Intelligence

Towards Neuromorphic Machine Intelligence PDF Author: Hong Qu
Publisher: Elsevier
ISBN: 0443328218
Category : Computers
Languages : en
Pages : 222

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Book Description
Towards Neuromorphic Machine Intelligence: Spike-Based Representation, Learning, and Applications provides readers with in-depth understanding of Spiking Neural Networks (SNNs), which is a burgeoning research branch of Artificial Neural Networks (ANNs), AI, and Machine Learning that sits at the heart of the integration between Computer Science and Neural Engineering. In recent years, neural networks have re-emerged in relation to AI, representing a well-grounded paradigm rooted in disciplines from physics and psychology to information science and engineering.This book represents one of the established cross-over areas where neurophysiology, cognition, and neural engineering coincide with the development of new Machine Learning and AI paradigms. There are many excellent theoretical achievements in neuron models, learning algorithms, network architecture, and so on. But these achievements are numerous and scattered, with a lack of straightforward systematic integration, making it difficult for researchers to assimilate and apply. As the third generation of Artificial Neural Networks (ANNs), Spiking Neural Networks (SNNs) simulate the neuron dynamics and information transmission in a biological neural system in more detail, which is a cross-product of computer science and neuroscience. The primary target audience of this book is divided into two categories: artificial intelligence researchers who know nothing about SNNs, and researchers who know a lot about SNNs. The former needs to acquire fundamental knowledge of SNNs, but the challenge is that much of the existing literature on SNNs only slightly mentions the basic knowledge of SNNs, or is too superficial, and this book gives a systematic explanation from scratch. The latter needs learning about some novel research achievements in the field of SNNs, and this book introduces the latest research results on different aspects of SNNs and provides detailed simulation processes to facilitate readers' replication. In addition, the book introduces neuromorphic hardware architecture as a further extension of the SNN system.The book starts with the birth and development of SNNs, and then introduces the main research hotspots, including spiking neuron models, learning algorithms, network architectures, and neuromorphic hardware. Therefore, the book provides readers with easy access to both the foundational concepts and recent research findings in SNNs. - Introduces Spiking Neural Networks (SNNs), a new generation of biologically inspired artificial intelligence. - Systematically presents basic concepts of SNNs, neuron and network models, learning algorithms, and neuromorphic hardware. - Introduces the latest research results on various aspects of SNNs and provides detailed simulation processes to facilitate readers' replication.

Innovations in Computer Vision and Data Classification

Innovations in Computer Vision and Data Classification PDF Author: Arfan Ghani
Publisher: Springer Nature
ISBN: 3031601408
Category : Classification rule mining
Languages : en
Pages : 159

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Book Description
This book delves into the dynamic realm of data classification, focusing on its real-world applications. Through an insightful journey, readers are introduced to the practical applications of reconfigurable hardware, machine learning, computer vision, and neuromorphic circuit design across diverse domains. The author explores topics such as the role of Field-Programmable Gate Arrays (FPGAs) in expediting pandemic data analysis and the transformative impact of computer vision on healthcare. Additionally, the book delves into environmental data classification, energy-efficient solutions for deep neural network applications, and real-time performance analysis of energy conversion algorithms. With the author's guidance, readers are led through practical implementations, ensuring a comprehensive grasp of each subject matter. Whether a seasoned researcher, engineer, or student, this book equips readers with the tools to make data-driven decisions, optimize systems, and innovate solutions across various fields, from healthcare to environmental monitoring. Explores advancements in data classification, encompassing FPGA acceleration, neuromorphic hardware, and computer vision-based diagnosis; Presents data classification through real-world examples from healthcare, environmental science, and energy conversion, employing applied machine learning and deep neural networks; Includes guidance on the application of complex concepts with ease through a didactic approach and hands-on instruction.

Vision: Images, Signals And Neural Networks - Models Of Neural Processing In Visual Perception

Vision: Images, Signals And Neural Networks - Models Of Neural Processing In Visual Perception PDF Author: Jeanny Herault
Publisher: World Scientific Publishing Company
ISBN: 9813107545
Category : Computers
Languages : en
Pages : 308

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Book Description
At the fascinating frontiers of neurobiology, mathematics and psychophysics, this book addresses the problem of human and computer vision on the basis of cognitive modeling. After recalling the physics of light and its transformation through media and optics, Hérault presents the principles of the primate's visual system in terms of anatomy and functionality. Then, the neuronal circuitry of the retina is analyzed in terms of spatio-temporal filtering. This basic model is extended to the concept of neuromorphic circuits for motion processing and to the processing of color in the retina. For more in-depth studies, the adaptive non-linear properties of the photoreceptors and of ganglion cells are addressed, exhibiting all the power of the retinal pre-processing of images as a system of information cleaning suitable for further cortical processing. As a target of retinal information, the primary visual area is presented as a bank of filters able to extract valuable descriptors of images, suitable for categorization and recognition and also for local information extraction such as saliency and perspective. All along the book, many comparisons between the models and human perception are discussed as well as detailed applications to computer vision./a