| 书目名称 | Computer Vision Using Deep Learning | | 副标题 | Neural Network Archi | | 编辑 | Vaibhav Verdhan | | 视频video | | | 概述 | Implement Deep Learning solutions on your own systems to bridge the gap between theory and practice.Examine the inner workings of the codes and libraries that make Deep Learning applications work.Crea | | 图书封面 |  | | 描述 | .Organizations spend huge resources in developing software that can perform the way a human does. Image classification, object detection and tracking, pose estimation, facial recognition, and sentiment estimation all play a major role in solving computer vision problems. .This book will bring into focus these and other deep learning architectures and techniques to help you create solutions using Keras and the TensorFlow library. You‘ll also review mutliple neural network architectures, including LeNet, AlexNet, VGG, Inception, R-CNN, Fast R-CNN, Faster R-CNN, Mask R-CNN, YOLO, and SqueezeNet and see how they work alongside Python code via best practices, tips, tricks, shortcuts, and pitfalls. All code snippets will be broken down and discussed thoroughly so you can implement the same principles in your respective environments..Computer Vision Using Deep Learning. offers a comprehensive yet succinct guide that stitches DL and CV together to automate operations, reduce human intervention, increase capability, and cut the costs. .What You‘ll Learn.Examine deep learning code and concepts to apply guiding principals to your own projects.Classify and evaluate various architectures to bet | | 出版日期 | Book 2021 | | 关键词 | Deep Learning; Computer vision; Artificial Intelligence; AI; Object Detection; Image Classification; Pose | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-4842-6616-8 | | isbn_softcover | 978-1-4842-6615-1 | | isbn_ebook | 978-1-4842-6616-8 | | copyright | Vaibhav Verdhan 2021 |
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发表于 2025-3-21 19:40:31
