Deep Learning Applications With Practical Measured Results In Electron

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Deep Learning Applications with Practical Measured Results in Electronics Industries

Mong-Fong Horng,Hsu-Yang Kung,Chi-Hua Chen,Feng-Jang Hwang

Author : Mong-Fong Horng,Hsu-Yang Kung,Chi-Hua Chen,Feng-Jang Hwang
Publisher : MDPI
Page : 272 pages
File Size : 48,6 Mb
Release : 2020-05-22
Category : Technology & Engineering
ISBN : 9783039288632

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Deep Learning Applications with Practical Measured Results in Electronics Industries by Mong-Fong Horng,Hsu-Yang Kung,Chi-Hua Chen,Feng-Jang Hwang Pdf

This book collects 14 articles from the Special Issue entitled “Deep Learning Applications with Practical Measured Results in Electronics Industries” of Electronics. Topics covered in this Issue include four main parts: (1) environmental information analyses and predictions, (2) unmanned aerial vehicle (UAV) and object tracking applications, (3) measurement and denoising techniques, and (4) recommendation systems and education systems. These authors used and improved deep learning techniques (e.g., ResNet (deep residual network), Faster-RCNN (faster regions with convolutional neural network), LSTM (long short term memory), ConvLSTM (convolutional LSTM), GAN (generative adversarial network), etc.) to analyze and denoise measured data in a variety of applications and services (e.g., wind speed prediction, air quality prediction, underground mine applications, neural audio caption, etc.). Several practical experiments were conducted, and the results indicate that the performance of the presented deep learning methods is improved compared with the performance of conventional machine learning methods.

Deep Learning Applications with Practical Measured Results in Electronics Industries

Mong-Fong Horng,Hsu-Yang Kung,Chi-Hua Chen,Feng-Jang Hwang

Author : Mong-Fong Horng,Hsu-Yang Kung,Chi-Hua Chen,Feng-Jang Hwang
Publisher : Unknown
Page : 272 pages
File Size : 42,7 Mb
Release : 2020
Category : Engineering (General). Civil engineering (General)
ISBN : 3039288644

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Deep Learning Applications with Practical Measured Results in Electronics Industries by Mong-Fong Horng,Hsu-Yang Kung,Chi-Hua Chen,Feng-Jang Hwang Pdf

This book collects 14 articles from the Special Issue entitled “Deep Learning Applications with Practical Measured Results in Electronics Industries” of Electronics. Topics covered in this Issue include four main parts: (1) environmental information analyses and predictions, (2) unmanned aerial vehicle (UAV) and object tracking applications, (3) measurement and denoising techniques, and (4) recommendation systems and education systems. These authors used and improved deep learning techniques (e.g., ResNet (deep residual network), Faster-RCNN (faster regions with convolutional neural network), LSTM (long short term memory), ConvLSTM (convolutional LSTM), GAN (generative adversarial network), etc.) to analyze and denoise measured data in a variety of applications and services (e.g., wind speed prediction, air quality prediction, underground mine applications, neural audio caption, etc.). Several practical experiments were conducted, and the results indicate that the performance of the presented deep learning methods is improved compared with the performance of conventional machine learning methods.

Advances in Deep Learning Applications for Smart Cities

Kumar, Rajeev,Dwivedi, Rakesh Kumar

Author : Kumar, Rajeev,Dwivedi, Rakesh Kumar
Publisher : IGI Global
Page : 335 pages
File Size : 52,9 Mb
Release : 2022-05-13
Category : Political Science
ISBN : 9781799897125

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Advances in Deep Learning Applications for Smart Cities by Kumar, Rajeev,Dwivedi, Rakesh Kumar Pdf

Within the past decade, technology has grown exponentially, and governments have promoted smart cities. Emerging smart cities have become both crucibles and showrooms for the practical application of the internet of things (IoT), cloud computing, and the integration of big data into everyday life. This complex concoction requires new thinking of the synergistic utilization of deep learning and blockchain methods and data-driven decision making with automation infrastructure, autonomous transportation, and more. Advances in Deep Learning Applications for Smart Cities provides a global perspective on current and future trends concerning the integration of deep learning and blockchain for smart cities. It provides valuable insights on the best practices and success factors for smart cities. Covering topics such as digital healthcare, object detection methods, and power consumption, this book is an excellent reference for researchers, scientists, libraries, industry experts, government organizations, students and educators of higher education, business professionals, communication and marketing agencies, entrepreneurs, and academicians.

Deep Learning Applications

Pier Luigi Mazzeo,Paolo Spagnolo

Author : Pier Luigi Mazzeo,Paolo Spagnolo
Publisher : BoD – Books on Demand
Page : 216 pages
File Size : 42,8 Mb
Release : 2021-07-14
Category : Computers
ISBN : 9781839623745

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Deep Learning Applications by Pier Luigi Mazzeo,Paolo Spagnolo Pdf

Deep learning is a branch of machine learning similar to artificial intelligence. The applications of deep learning vary from medical imaging to industrial quality checking, sports, and precision agriculture. This book is divided into two sections. The first section covers deep learning architectures and the second section describes the state of the art of applications based on deep learning.

Machine Learning and Deep Learning in Real-Time Applications

Mahrishi, Mehul,Hiran, Kamal Kant,Meena, Gaurav,Sharma, Paawan

Author : Mahrishi, Mehul,Hiran, Kamal Kant,Meena, Gaurav,Sharma, Paawan
Publisher : IGI Global
Page : 344 pages
File Size : 53,8 Mb
Release : 2020-04-24
Category : Computers
ISBN : 9781799830979

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Machine Learning and Deep Learning in Real-Time Applications by Mahrishi, Mehul,Hiran, Kamal Kant,Meena, Gaurav,Sharma, Paawan Pdf

Artificial intelligence and its various components are rapidly engulfing almost every professional industry. Specific features of AI that have proven to be vital solutions to numerous real-world issues are machine learning and deep learning. These intelligent agents unlock higher levels of performance and efficiency, creating a wide span of industrial applications. However, there is a lack of research on the specific uses of machine/deep learning in the professional realm. Machine Learning and Deep Learning in Real-Time Applications provides emerging research exploring the theoretical and practical aspects of machine learning and deep learning and their implementations as well as their ability to solve real-world problems within several professional disciplines including healthcare, business, and computer science. Featuring coverage on a broad range of topics such as image processing, medical improvements, and smart grids, this book is ideally designed for researchers, academicians, scientists, industry experts, scholars, IT professionals, engineers, and students seeking current research on the multifaceted uses and implementations of machine learning and deep learning across the globe.

Big Data Analysis and Deep Learning Applications

Thi Thi Zin,Jerry Chun-Wei Lin

Author : Thi Thi Zin,Jerry Chun-Wei Lin
Publisher : Springer
Page : 386 pages
File Size : 55,8 Mb
Release : 2018-06-06
Category : Technology & Engineering
ISBN : 9789811308697

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Big Data Analysis and Deep Learning Applications by Thi Thi Zin,Jerry Chun-Wei Lin Pdf

This book presents a compilation of selected papers from the first International Conference on Big Data Analysis and Deep Learning Applications (ICBDL 2018), and focuses on novel techniques in the fields of big data analysis, machine learning, system monitoring, image processing, conventional neural networks, communication, industrial information, and their applications. Readers will find insights to help them realize more efficient algorithms and systems used in real-life applications and contexts, making the book an essential reference guide for academic researchers, professionals, software engineers in the industry, and regulators of aviation authorities.

Trends in Deep Learning Methodologies

Vincenzo Piuri,Sandeep Raj,Angelo Genovese,Rajshree Srivastava

Author : Vincenzo Piuri,Sandeep Raj,Angelo Genovese,Rajshree Srivastava
Publisher : Academic Press
Page : 308 pages
File Size : 54,7 Mb
Release : 2020-11-12
Category : Computers
ISBN : 9780128232682

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Trends in Deep Learning Methodologies by Vincenzo Piuri,Sandeep Raj,Angelo Genovese,Rajshree Srivastava Pdf

Trends in Deep Learning Methodologies: Algorithms, Applications, and Systems covers deep learning approaches such as neural networks, deep belief networks, recurrent neural networks, convolutional neural networks, deep auto-encoder, and deep generative networks, which have emerged as powerful computational models. Chapters elaborate on these models which have shown significant success in dealing with massive data for a large number of applications, given their capacity to extract complex hidden features and learn efficient representation in unsupervised settings. Chapters investigate deep learning-based algorithms in a variety of application, including biomedical and health informatics, computer vision, image processing, and more. In recent years, many powerful algorithms have been developed for matching patterns in data and making predictions about future events. The major advantage of deep learning is to process big data analytics for better analysis and self-adaptive algorithms to handle more data. Deep learning methods can deal with multiple levels of representation in which the system learns to abstract higher level representations of raw data. Earlier, it was a common requirement to have a domain expert to develop a specific model for each specific application, however, recent advancements in representation learning algorithms allow researchers across various subject domains to automatically learn the patterns and representation of the given data for the development of specific models. Provides insights into the theory, algorithms, implementation and the application of deep learning techniques Covers a wide range of applications of deep learning across smart healthcare and smart engineering Investigates the development of new models and how they can be exploited to find appropriate solutions

Deep Neural Network Applications

Hasmik Osipyan,Bosede Iyiade Edwards,Adrian David Cheok

Author : Hasmik Osipyan,Bosede Iyiade Edwards,Adrian David Cheok
Publisher : CRC Press
Page : 158 pages
File Size : 49,9 Mb
Release : 2022-04-28
Category : Computers
ISBN : 9780429556203

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Deep Neural Network Applications by Hasmik Osipyan,Bosede Iyiade Edwards,Adrian David Cheok Pdf

The world is on the verge of fully ushering in the fourth industrial revolution, of which artificial intelligence (AI) is the most important new general-purpose technology. Like the steam engine that led to the widespread commercial use of driving machineries in the industries during the first industrial revolution; the internal combustion engine that gave rise to cars, trucks, and airplanes; electricity that caused the second industrial revolution through the discovery of direct and alternating current; and the Internet, which led to the emergence of the information age, AI is a transformational technology. It will cause a paradigm shift in the way’s problems are solved in every aspect of our lives, and, from it, innovative technologies will emerge. AI is the theory and development of machines that can imitate human intelligence in tasks such as visual perception, speech recognition, decision-making, and human language translation. This book provides a complete overview on the deep learning applications and deep neural network architectures. It also gives an overview on most advanced future-looking fundamental research in deep learning application in artificial intelligence. Research overview includes reasoning approaches, problem solving, knowledge representation, planning, learning, natural language processing, perception, motion and manipulation, social intelligence and creativity. It will allow the reader to gain a deep and broad knowledge of the latest engineering technologies of AI and Deep Learning and is an excellent resource for academic research and industry applications.

Deep Learning Applications in Image Analysis

Sanjiban Sekhar Roy,Ching-Hsien Hsu,Venkateshwara Kagita

Author : Sanjiban Sekhar Roy,Ching-Hsien Hsu,Venkateshwara Kagita
Publisher : Springer Nature
Page : 218 pages
File Size : 44,9 Mb
Release : 2023-07-08
Category : Technology & Engineering
ISBN : 9789819937844

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Deep Learning Applications in Image Analysis by Sanjiban Sekhar Roy,Ching-Hsien Hsu,Venkateshwara Kagita Pdf

This book provides state-of-the-art coverage of deep learning applications in image analysis. The book demonstrates various deep learning algorithms that can offer practical solutions for various image-related problems; also how these algorithms are used by scientists and scholars in industry and academia. This includes autoencoder and deep convolutional generative adversarial network in improving classification performance of Bangla handwritten characters, dealing with deep learning-based approaches using feature selection methods for automatic diagnosis of covid-19 disease from x-ray images, imbalance image data sets of classification, image captioning using deep transfer learning, developing a vehicle over speed detection system, creating an intelligent system for video-based proximity analysis, building a melanoma cancer detection system using deep learning, plant diseases classification using AlexNet, dealing with hyperspectral images using deep learning, chest x-ray image classification of pneumonia disease using efficient net and inceptionv3. The book also addresses the difficulty of implementing deep learning in terms of computation time and the complexity of reasoning and modelling different types of data where information is currently encoded. Each chapter has the application of various new or existing deep learning models such as Deep Neural Network (DNN) and Deep Convolutional Neural Networks (DCNN). The detailed utilization of deep learning packages that are available in MATLAB, Python and R programming environments have also been discussed, therefore, the readers will get to know about the practical implementation of deep learning as well. The content of this book is presented in a simple and lucid style for professionals, nonprofessionals, scientists, and students interested in the research area of deep learning applications in image analysis.

Examining the Impact of Deep Learning and IoT on Multi-Industry Applications

Raut, Roshani,Mihovska, Albena Dimitrova

Author : Raut, Roshani,Mihovska, Albena Dimitrova
Publisher : IGI Global
Page : 304 pages
File Size : 46,8 Mb
Release : 2021-01-29
Category : Computers
ISBN : 9781799875178

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Examining the Impact of Deep Learning and IoT on Multi-Industry Applications by Raut, Roshani,Mihovska, Albena Dimitrova Pdf

Deep learning, as a recent AI technique, has proven itself efficient in solving many real-world problems. Deep learning algorithms are efficient, high performing, and an effective standard for solving these problems. In addition, with IoT, deep learning is in many emerging and developing domains of computer technology. Deep learning algorithms have brought a revolution in computer vision applications by introducing an efficient solution to several image processing-related problems that have long remained unresolved or moderately solved. Various significant IoT technologies in various industries, such as education, health, transportation, and security, combine IoT with deep learning for complex problem solving and the supported interaction between human beings and their surroundings. Examining the Impact of Deep Learning and IoT on Multi-Industry Applications provides insights on how deep learning, together with IoT, impacts various sectors such as healthcare, agriculture, cyber security, and social media analysis applications. The chapters present solutions to various real-world problems using these methods from various researchers’ points of view. While highlighting topics such as medical diagnosis, power consumption, livestock management, security, and social media analysis, this book is ideal for IT specialists, technologists, security analysts, medical practitioners, imaging specialists, diagnosticians, academicians, researchers, industrial experts, scientists, and undergraduate and postgraduate students who are working in the field of computer engineering, electronics, and electrical engineering.

Applications in Electronics Pervading Industry, Environment and Society

Sergio Saponara,Alessandro De Gloria

Author : Sergio Saponara,Alessandro De Gloria
Publisher : Springer Nature
Page : 340 pages
File Size : 55,6 Mb
Release : 2022-04-09
Category : Technology & Engineering
ISBN : 9783030954987

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Applications in Electronics Pervading Industry, Environment and Society by Sergio Saponara,Alessandro De Gloria Pdf

This book provides a thorough overview of cutting-edge research on electronics applications relevant to industry, the environment, and society at large. It covers a broad spectrum of application domains, from automotive to space and from health to security, while devoting special attention to the use of embedded devices and sensors for imaging, communication and control. The volume is based on the 2021 ApplePies Conference, held online in September 2021, which brought together researchers and stakeholders to consider the most significant current trends in the field of applied electronics and to debate visions for the future. Areas addressed by the conference included information communication technology; biotechnology and biomedical imaging; space; secure, clean and efficient energy; the environment; and smart, green and integrated transport. As electronics technology continues to develop apace, constantly meeting previously unthinkable targets, further attention needs to be directed toward the electronics applications and the development of systems that facilitate human activities. This book, written by industrial and academic professionals, represents a valuable contribution in this endeavor.

Electronic Nose Technologies and Advances in Machine Olfaction

Albastaki, Yousif,Albalooshi, Fatema

Author : Albastaki, Yousif,Albalooshi, Fatema
Publisher : IGI Global
Page : 318 pages
File Size : 53,5 Mb
Release : 2018-04-13
Category : Technology & Engineering
ISBN : 9781522538639

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Electronic Nose Technologies and Advances in Machine Olfaction by Albastaki, Yousif,Albalooshi, Fatema Pdf

The design and study of materials is a pivotal component to new discoveries in the various fields of science and technology. By better understanding the components and structures of materials, researchers can increase its applications across different industries. Electronic Nose Technologies and Advances in Machine Olfaction is an academic scholarly resource that examines the emerging applications of odor-sensing devices as well as a better understanding of the designing process with the aid of neural networks and various other technologies. Featuring coverage on a broad range of topics including food spoilage detection, chemical sensing, and olfactometer, this book is a vital resource for engineers, academicians, researchers, students, and practitioners seeking current research on the advancements in applications of odor-sensing devices.

Design of Intelligent Applications Using Machine Learning and Deep Learning Techniques

Ramchandra Sharad Mangrulkar,Antonis Michalas,Narendra Shekokar,Meera Narvekar,Pallavi Vijay Chavan

Author : Ramchandra Sharad Mangrulkar,Antonis Michalas,Narendra Shekokar,Meera Narvekar,Pallavi Vijay Chavan
Publisher : CRC Press
Page : 432 pages
File Size : 42,7 Mb
Release : 2021
Category : Computers
ISBN : 1003133681

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Design of Intelligent Applications Using Machine Learning and Deep Learning Techniques by Ramchandra Sharad Mangrulkar,Antonis Michalas,Narendra Shekokar,Meera Narvekar,Pallavi Vijay Chavan Pdf

Machine learning (ML) and deep learning (DL) algorithms are invaluable resources for Industry 4.0 and allied areas and are considered as the future of computing. A subfield called neural networks, to recognize and understand patterns in data, helps a machine carry out tasks in a manner similar to humans. The intelligent models developed using ML and DL are effectively designed and are fully investigated - bringing in practical applications in many fields such as health care, agriculture and security. These algorithms can only be successfully applied in the context of data computing and analysis. Today, ML and DL have created conditions for potential developments in detection and prediction. Apart from these domains, ML and DL are found useful in analysing the social behaviour of humans. With the advancements in the amount and type of data available for use, it became necessary to build a means to process the data and that is where deep neural networks prove their importance. These networks are capable of handling a large amount of data in such fields as finance and images. This book also exploits key applications in Industry 4.0 including: · Fundamental models, issues and challenges in ML and DL. · Comprehensive analyses and probabilistic approaches for ML and DL. · Various applications in healthcare predictions such as mental health, cancer, thyroid disease, lifestyle disease and cardiac arrhythmia. · Industry 4.0 applications such as facial recognition, feather classification, water stress prediction, deforestation control, tourism and social networking. · Security aspects of Industry 4.0 applications suggest remedial actions against possible attacks and prediction of associated risks. - Information is presented in an accessible way for students, researchers and scientists, business innovators and entrepreneurs, sustainable assessment and management professionals. This book equips readers with a knowledge of data analytics, ML and DL techniques for applications defined under the umbrella of Industry 4.0. This book offers comprehensive coverage, promising ideas and outstanding research contributions, supporting further development of ML and DL approaches by applying intelligence in various applications.

Scale Space and Variational Methods in Computer Vision

Luca Calatroni,Marco Donatelli,Serena Morigi,Marco Prato,Matteo Santacesaria

Author : Luca Calatroni,Marco Donatelli,Serena Morigi,Marco Prato,Matteo Santacesaria
Publisher : Springer Nature
Page : 767 pages
File Size : 55,5 Mb
Release : 2023-05-09
Category : Computers
ISBN : 9783031319754

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Scale Space and Variational Methods in Computer Vision by Luca Calatroni,Marco Donatelli,Serena Morigi,Marco Prato,Matteo Santacesaria Pdf

This book constitutes the proceedings of the 9th International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2023, which took place in Santa Margherita di Pula, Italy, in May 2023. The 57 papers presented in this volume were carefully reviewed and selected from 72 submissions. They were organized in topical sections as follows: Inverse Problems in Imaging; Machine and Deep Learning in Imaging; Optimization for Imaging: Theory and Methods; Scale Space, PDEs, Flow, Motion and Registration.

Deep Learning, Machine Learning and IoT in Biomedical and Health Informatics

Sujata Dash,Subhendu Kumar Pani,Joel J. P. C. Rodrigues,Babita Majhi

Author : Sujata Dash,Subhendu Kumar Pani,Joel J. P. C. Rodrigues,Babita Majhi
Publisher : CRC Press
Page : 407 pages
File Size : 46,6 Mb
Release : 2022-02-10
Category : Computers
ISBN : 9781000534054

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Deep Learning, Machine Learning and IoT in Biomedical and Health Informatics by Sujata Dash,Subhendu Kumar Pani,Joel J. P. C. Rodrigues,Babita Majhi Pdf

Biomedical and Health Informatics is an important field that brings tremendous opportunities and helps address challenges due to an abundance of available biomedical data. This book examines and demonstrates state-of-the-art approaches for IoT and Machine Learning based biomedical and health related applications. This book aims to provide computational methods for accumulating, updating and changing knowledge in intelligent systems and particularly learning mechanisms that help us to induce knowledge from the data. It is helpful in cases where direct algorithmic solutions are unavailable, there is lack of formal models, or the knowledge about the application domain is inadequately defined. In the future IoT has the impending capability to change the way we work and live. These computing methods also play a significant role in design and optimization in diverse engineering disciplines. With the influence and the development of the IoT concept, the need for AI (artificial intelligence) techniques has become more significant than ever. The aim of these techniques is to accept imprecision, uncertainties and approximations to get a rapid solution. However, recent advancements in representation of intelligent IoTsystems generate a more intelligent and robust system providing a human interpretable, low-cost, and approximate solution. Intelligent IoT systems have demonstrated great performance to a variety of areas including big data analytics, time series, biomedical and health informatics. This book will be very beneficial for the new researchers and practitioners working in the biomedical and healthcare fields to quickly know the best performing methods. It will also be suitable for a wide range of readers who may not be scientists but who are also interested in the practice of such areas as medical image retrieval, brain image segmentation, among others. • Discusses deep learning, IoT, machine learning, and biomedical data analysis with broad coverage of basic scientific applications • Presents deep learning and the tremendous improvement in accuracy, robustness, and cross- language generalizability it has over conventional approaches • Discusses various techniques of IoT systems for healthcare data analytics • Provides state-of-the-art methods of deep learning, machine learning and IoT in biomedical and health informatics • Focuses more on the application of algorithms in various real life biomedical and engineering problems

Deep Learning Applications With Practical Measured Results In Electronics Industries

Deep Learning Applications with Practical Measured Results in Electronics Industries by Mong-Fong Horng,Hsu-Yang Kung,Chi-Hua Chen,Feng-Jang Hwang Pdf

Deep Learning Applications with Practical Measured Results in Electronics Industries by Mong-Fong Horng,Hsu-Yang Kung,Chi-Hua Chen,Feng-Jang Hwang Pdf

Advances in Deep Learning Applications for Smart Cities by Kumar, Rajeev,Dwivedi, Rakesh Kumar Pdf

Deep Learning Applications by Pier Luigi Mazzeo,Paolo Spagnolo Pdf

Machine Learning and Deep Learning in Real-Time Applications by Mahrishi, Mehul,Hiran, Kamal Kant,Meena, Gaurav,Sharma, Paawan Pdf

Big Data Analysis and Deep Learning Applications by Thi Thi Zin,Jerry Chun-Wei Lin Pdf

Trends in Deep Learning Methodologies by Vincenzo Piuri,Sandeep Raj,Angelo Genovese,Rajshree Srivastava Pdf

Deep Neural Network Applications by Hasmik Osipyan,Bosede Iyiade Edwards,Adrian David Cheok Pdf

Deep Learning Applications in Image Analysis by Sanjiban Sekhar Roy,Ching-Hsien Hsu,Venkateshwara Kagita Pdf

Examining the Impact of Deep Learning and IoT on Multi-Industry Applications by Raut, Roshani,Mihovska, Albena Dimitrova Pdf

Applications in Electronics Pervading Industry, Environment and Society by Sergio Saponara,Alessandro De Gloria Pdf

Electronic Nose Technologies and Advances in Machine Olfaction by Albastaki, Yousif,Albalooshi, Fatema Pdf

Design of Intelligent Applications Using Machine Learning and Deep Learning Techniques by Ramchandra Sharad Mangrulkar,Antonis Michalas,Narendra Shekokar,Meera Narvekar,Pallavi Vijay Chavan Pdf

Scale Space and Variational Methods in Computer Vision by Luca Calatroni,Marco Donatelli,Serena Morigi,Marco Prato,Matteo Santacesaria Pdf

Deep Learning, Machine Learning and IoT in Biomedical and Health Informatics by Sujata Dash,Subhendu Kumar Pani,Joel J. P. C. Rodrigues,Babita Majhi Pdf

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