PyTorch Computer Vision Cookbook

Avendi, Michael

PyTorch Computer Vision Cookbook
  • 出版商: Packt Publishing
  • 出版日期: 2020-03-20
  • 售價: $1,840
  • 貴賓價: 9.5 折 $1,748
  • 語言: 英文
  • 頁數: 364
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1838644830
  • ISBN-13: 9781838644833
  • 相關分類: DeepLearning、Computer Vision

    • 海外代購書籍(需單獨結帳)

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商品描述

Computer vision techniques play an integral role in helping developers gain a high-level understanding of digital images and videos. With this book, you’ll learn how to solve the trickiest problems in computer vision (CV) using the power of deep learning algorithms, and leverage the latest features of PyTorch 1.x to perform a variety of CV tasks.

 

Starting with a quick overview of the PyTorch library and key deep learning concepts, the book then covers common and not-so-common challenges faced while performing image recognition, image segmentation, object detection, image generation, and other tasks. Next, you’ll understand how to implement these tasks using various deep learning architectures such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), long short-term memory (LSTM), and generative adversarial networks (GANs). Using a problem-solution approach, you’ll learn how to solve any issue you might face while fine-tuning the performance of a model or integrating it into your application. Later, you’ll get to grips with scaling your model to handle larger workloads, and implementing best practices for training models efficiently.

 

By the end of this CV book, you’ll be proficient in confidently solving many CV related problems using deep learning and PyTorch.

商品描述(中文翻譯)

電腦視覺技術在幫助開發者對數位影像和影片進行高層次理解方面扮演著重要角色。這本書將教你如何運用深度學習演算法以及利用 PyTorch 1.x 的最新功能來解決電腦視覺 (CV) 領域中最棘手的問題，並執行各種 CV 任務。

首先，書籍將快速概述 PyTorch 函式庫和關鍵的深度學習概念，然後介紹在執行圖像識別、圖像分割、物體檢測、圖像生成等任務時所面臨的常見和不太常見的挑戰。接下來，你將了解如何使用各種深度學習架構來實現這些任務，例如卷積神經網絡 (CNN)、循環神經網絡 (RNN)、長短期記憶 (LSTM) 和生成對抗網絡 (GAN)。通過問題解決的方式，你將學習如何解決在調整模型性能或將其整合到應用程式中時可能遇到的任何問題。隨後，你將掌握將模型擴展以處理更大工作量的技巧，並實施有效訓練模型的最佳實踐。

通過閱讀這本電腦視覺書籍，你將能夠自信地運用深度學習和 PyTorch 解決許多與 CV 相關的問題。

作者簡介

Michael Avendi is a principal data scientist with vast experience in deep learning, computer vision, and medical imaging analysis. He works on the research and development of data-driven algorithms for various imaging problems, including medical imaging applications. His research papers have been published in major medical journals, including the Medical Imaging Analysis journal. Michael Avendi is an active Kaggle participant and was awarded a top prize in a Kaggle competition in 2017.

作者簡介(中文翻譯)

Michael Avendi 是一位資深的資料科學家，擁有豐富的深度學習、電腦視覺和醫學影像分析經驗。他致力於研究和開發基於數據的演算法，應用於各種影像問題，包括醫學影像應用。他的研究論文已發表在主要的醫學期刊，包括《醫學影像分析》期刊。Michael Avendi 是一位活躍的 Kaggle 參賽者，並在2017年的一場 Kaggle 競賽中獲得了頂級獎項。

目錄大綱

  1. Getting Started with PyTorch for Deep Learning
  2. Binary Image Classification
  3. Multi-class Image Classification
  4. Single-object detection
  5. Multi-object detection
  6. Single-object Segmentation
  7. Multi-object Segmentation
  8. Neural Style Transfer with PyTorch
  9. GANs and Adversarial Examples
  10. Video Processing with PyTorch

目錄大綱(中文翻譯)

- 使用 PyTorch 進行深度學習入門
- 二元圖像分類
- 多類別圖像分類
- 單一物體偵測
- 多物體偵測
- 單一物體分割
- 多物體分割
- 使用 PyTorch 進行神經風格轉換
- GANs 和對抗性範例
- 使用 PyTorch 進行影片處理

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