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Deep Learning and Convolutional Neural Networks for Medical Image Computing

in medical image computing, and large-scale radiology database mining. A particular focus is placed on the application of convolutional neural;

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Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics

formation and enhancement, image understanding, visual recognition in medical applications, statistical learning, deep neural networks, structured;

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Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics

formation and enhancement, image understanding, visual recognition in medical applications, statistical learning, deep neural networks, structured;

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Convolutional Neural Networks in Visual Computing

guide to engineers or students who want to have a quick start on learning and/or building deep learning systems. This book provides a good;

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Convolutional Neural Networks in Visual Computing

guide to engineers or students who want to have a quick start on learning and/or building deep learning systems. This book provides a good;

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Deep Learning and Practice with MindSpore

AI computing framework. Divided into 14 chapters, the book covers deep learning, deep neural networks (DNNs), convolutional neural networks;

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Deep Learning and Practice with MindSpore

AI computing framework. Divided into 14 chapters, the book covers deep learning, deep neural networks (DNNs), convolutional neural networks;

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Neural Information Processing

follows: adversarial networks and learning; convolutional neural networks; deep neural networks; embeddings and feature fusion; human centred;

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Advanced Deep Learning with R

learning book starts by covering the essential deep learning techniques and concepts for prediction and classification. You will learn about neural;

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Hardware Accelerator Systems for Artificial Intelligence and Machine Learning

, Architecture of NPU for DNN, Hardware Architecture for Convolutional Neural Network for Image Processing, FPGA based Neural Network Accelerators, and;

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Hands-On Deep Learning with TensorFlow

about convolutional neural networks, and logistic regression while training models for deep learning to gain key insights into your data;

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Deep Learning Models for Medical Imaging

Deep Learning Models for Medical Imaging explains the concepts of Deep Learning (DL) and its importance in medical imaging and/or;

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Practical TensorFlow.js

learning products suitable for web browsers Work with deep learning algorithms such as feedforward neural networks, convolutional neural;

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Practical TensorFlow.js

learning products suitable for web browsers Work with deep learning algorithms such as feedforward neural networks, convolutional neural networks;

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Hands-On Convolutional Neural Networks with TensorFlow

of Convolutional Neural Networks Harness Python and Tensorflow to train CNNs Build scalable deep learning models that can process millions of items Book;

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Deep Learning from Scratch Building with Python from First Principles

With the resurgence of neural networks in the 2010s, deep learning has become essential for machine learning practitioners and even many;

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Deep Learning for Data Analytics

analyze large volumes of data for business, engineering, and biomedical applications. Deep learning architectures including deep neural networks;

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Neural Information Processing

; convolutional neural networks; deep neural networks; feature learning and representation; human centred computing; human centred computing and medicine;

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Deep Biometrics

Stacked Autoencoder, Convolutional Neural Networks, Generative Adversary Networks, and so on. The contributors demonstrate the power of deep;

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Deep Biometrics

Stacked Autoencoder, Convolutional Neural Networks, Generative Adversary Networks, and so on. The contributors demonstrate the power of deep;

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Hands-On Deep Learning for Images with TensorFlow

images Prepare your dataset for machine learning Create classical, convolutional, and deep neural networks Create a RESTful image classification;

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Hybrid Machine Intelligence for Medical Image Analysis

the latest trends in machine learning technologies and computational intelligence for intelligent medical image analysis. The topics covered;

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Tree-Based Convolutional Neural Networks

This book proposes a novel neural architecture, tree-based convolutional neural networks (TBCNNs),for processing tree-structured data;

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The Deep Learning Workshop

popular deep learning solutions. Finally, you'll get to grips with bidirectional recurrent neural networks (RNNs) and build generative adversarial;

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Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis

deep learning in clinical applicationsIntroduces several techniques for medical image processing and analysis for CAD systems design;

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Advanced Deep Learning with Python

models Understand DL techniques, such as meta-learning and graph neural networks Who this book is forThis book is for data scientists, deep;

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Einde inhoud

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