Deep Learning for Computer Vision

Rajalingappaa Shanmugamani

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商品描述

Key Features

  • Train efficient deep learning models to solve different problems in Computer Vision with the help of this comprehensive guide
  • Perform object detection, image classification and more, by combining the power of Python, Keras and Tensorflow
  • Contains practical examples using real-world datasets to apply the concepts of deep learning to various computer vision algorithms

Book Description

This book will not teach you what you already know - it directly jumps on to readying the environment required to train efficient deep learning models for a plethora of computer vision tasks such as object recognition, image classification and feature detection. In the process, you will leverage the power of Python, popular Deep Learning frameworks such as Keras and Tensorflow. You will implement the common architectures of deep learning such as convolutional neural networks, recurrent neural networks to work on your image data, with this book.

By the end of the book, you will be confident to develop and train your own deep learning models and use them to solve your Computer Vision problems.

What you will learn

  • Setup up the environment for keras and tensorflow
  • Train a pet classification problem while training the first deep learning model
  • Use a pre-trained model for image retrieval problem by understanding the deeper layers of a model
  • Learn about the solutions available of object detection and train a pedestrian detection to understand the nuances
  • Learn about losses for similarity learning and a train a model for face recognition
  • Train a model that can caption images by training image along with text
  • Advance the knowledge by learning Generative Adversarial Networks and train a model that can generate images
  • Explore video classification problem and relate video to images
  • Learn how to deploy the trained models across platforms

商品描述(中文翻譯)

主要特點



  • 使用這本全面指南,訓練高效的深度學習模型來解決計算機視覺中的不同問題

  • 通過結合Python、Keras和Tensorflow的力量,執行物體檢測、圖像分類等任務

  • 使用真實世界數據集的實際示例,將深度學習的概念應用於各種計算機視覺算法

書籍描述


這本書不會教你已經知道的知識 - 它直接著手準備環境,以訓練高效的深度學習模型,用於各種計算機視覺任務,如物體識別、圖像分類和特徵檢測。在此過程中,你將利用Python、流行的深度學習框架,如Keras和Tensorflow。你將使用本書來實現深度學習的常見架構,如卷積神經網絡、循環神經網絡,來處理圖像數據。


通過閱讀本書,你將有信心開發和訓練自己的深度學習模型,並用它們來解決計算機視覺問題。

你將學到什麼



  • 設置Keras和Tensorflow的環境

  • 在訓練第一個深度學習模型時,解決寵物分類問題

  • 通過理解模型的深層結構,使用預訓練模型解決圖像檢索問題

  • 了解物體檢測的解決方案,並訓練行人檢測模型以理解細微差異

  • 學習相似性學習的損失函數,並訓練人臉識別模型

  • 通過訓練圖像和文本,訓練能夠為圖像加上標題的模型

  • 通過學習生成對抗網絡,訓練能夠生成圖像的模型

  • 探索視頻分類問題,並將視頻與圖像相關聯

  • 學習如何在不同平台上部署訓練好的模型