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E-BooksHands–On Convolutional Neural Networks with TensorFlow (2024)



Hands–On Convolutional Neural Networks with TensorFlow (2024)
Free Download Iffat Zafar, Giounona Tzanidou, Richard Burton, "Hands-On Convolutional Neural Networks with TensorFlow: Solve computer vision problems with modeling in TensorFlow and Python"
English | 2018 | pages: 272 | ISBN: 1789130336 | EPUB | 27,0 mb
Learn how to apply TensorFlow to a wide range of deep learning and Machine Learning problems with this practical guide on training CNNs for image classification, image recognition, object detection and many computer vision challenges.



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Video TrainingDeep Learning Convolutional Neural Networks with Python (2024)



Deep Learning  Convolutional Neural Networks with Python (2024)
Free Download Deep Learning Convolutional Neural Networks with Python (2024)
Published 3/2024
Created by Dr. Mazhar Hussain
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 27 Lectures ( 4h 13m ) | Size: 2 GB



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E-BooksMunir A Accelerators for Convolutional Neural Networks 2023




Munir A  Accelerators for Convolutional Neural Networks 2023

Munir A Accelerators for Convolutional Neural Networks 2023 | 10.13 MB
N/A | 307 Pages

Title: Accelerators for Convolutional Neural Networks
Author: Munir, Arslan;Kong, Joonho;Qureshi, Mahmood Azhar;
Year: N/A




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E-BooksTeik T Convolutional Neural Networks for Medical Applications 2023




Teik T  Convolutional Neural Networks for Medical Applications 2023

Teik T Convolutional Neural Networks for Medical Applications 2023 | 4.62 MB
English | 103 Pages

Title: Convolutional Neural Networks for Medical Applications
Author: Charu C. Aggarwal
Year: 2018




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E-BooksConvolutional Neural Networks for Medical Applications



Convolutional Neural Networks for Medical Applications
Free Download Convolutional Neural Networks for Medical Applications
English | 2023 | ISBN: 9811988137 | 148 Pages | PDF EPUB (True) | 23 MB
Convolutional Neural Networks for Medical Applications consists of research investigated by the author, containing state-of-the-art knowledge, authored by Dr Teoh Teik Toe, in applying Convolutional Neural Networks (CNNs) to the medical imagery domain. This book will expose researchers to various applications and techniques applied with deep learning on medical images, as well as unique techniques to enhance the performance of these networks.Through the various chapters and topics covered, this book provides knowledge about the fundamentals of deep learning to a common reader while allowing a research scholar to identify some futuristic problem areas. The topics covered include brain tumor classification, pneumonia image classification, white blood cell classification, skin cancer classification and diabetic retinopathy detection. The first chapter will begin by introducing various topics used in training CNNs to help readers with common concepts covered across the book. Each chapter begins by providing information about the disease, its implications to the affected and how the use of CNNs can help to tackle issues faced in healthcare. Readers would be exposed to various performance enhancement techniques, which have been tried and tested successfully, such as specific data augmentations and image processing techniques utilized to improve the accuracy of the models.



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E-BooksNaved M IoT-enabled Convolutional Neural Networks Techniques and App 2023




Naved M  IoT-enabled Convolutional Neural Networks Techniques and App 2023

Naved M IoT-enabled Convolutional Neural Networks Techniques and App 2023 | 38.37 MB
English | 409 Pages

Title: IoT-enabled Convolutional Neural Networks: Techniques and Applications
Author: Mohd Naved
Year: 2018




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Video TrainingNeural Networks and Convolutional Neural Networks Essential Training



Neural Networks and Convolutional Neural Networks Essential Training
Free Download Neural Networks and Convolutional Neural Networks Essential Training
Duration: 1h 19m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 225 MB
Level: Intermediate | Genre: eLearning | Language: English
Take a deep dive into neural networks and convolutional neural networks, two key concepts in the area of machine learning. In this hands-on course, instructor Jonathan Fernandes covers fundamental neural and convolutional neural network concepts. Jonathan begins by providing an introduction to the components of neural networks, discussing activation functions and backpropagation. He then looks at convolutional neural networks, explaining why they're particularly good at image recognition tasks. He also steps through how to build a neural network model using Keras. Plus, learn about VGG16, the history of the ImageNet challenge, and more.
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Video TrainingConvolutional Neural Networks Deep Learning



Convolutional Neural Networks Deep Learning
Published 12/2022
Created by Sujithkumar MA
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 23 Lectures ( 2h 38m ) | Size: 1.27 GB



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E-BooksConvolutional Calculus



Convolutional Calculus
Convolutional Calculus by Ivan H. Dimovski
English | PDF | 1990 | 196 Pages | ISBN : 9401067236 | 31.9 MB
The series is divergent; therefore we may be sense'. able to do something with it. Eric T. Bell O. Heaviside Mathematics is a tool for thought. A highly necessary tool in a world where both feedback and non linearities abound. Similarly, all kinds of parts of mathematics serve as tools for other parts and for other sciences. Applying a simple rewriting rule to the quote on the right above one finds such statements as: 'One service topology has rendered mathematical physics .. .'; 'One service logic has rendered com puter science .. .'; 'One service category theory has rendered mathematics .. .'. All arguably true. And all statements obtainable this way form part of the raison d'etre of this series.



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E-BooksConvolutional Neural Networks for Medical Image Processing Applications



Convolutional Neural Networks for Medical Image Processing Applications
English | 2022 | ISBN: 978-1032104003 | 275 pages | True PDF | 16.01 MB
The rise in living standards increases the expectation of people in almost every field. At the forefront is health. Over the past few centuries, there have been major developments in healthcare. Medical device technology and developments in artificial intelligence (AI) are among the most important ones. The improving technology and our ability to harness the technology effectively by means such as AI have led to unprecedented advances, resulting in early diagnosis of diseases. AI algorithms enable the fast and early evaluation of images from medical devices to maximize the benefits.
While developments in the field of AI were quickly adapted to the field of health, in some cases this contributed to the formation of innovative artificial intelligence algorithms. Today, the most effective artificial intelligence method is accepted as deep learning. Convolutional neural network (CNN) architectures are deep learning algorithms used for image processing. This book contains applications of CNN methods. The content is quite extensive, including the application of different CNN methods to various medical image processing problems. Readers will be able to analyze the effects of CNN methods presented in the book in medical applications.



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