Hands-On Java Deep Learning for Computer Vision

Ramo, Klevis

  • 出版商: Packt Publishing
  • 出版日期: 2019-02-22
  • 售價: $1,300
  • 貴賓價: 9.5$1,235
  • 語言: 英文
  • 頁數: 260
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1789613965
  • ISBN-13: 9781789613964
  • 相關分類: Java 程式語言DeepLearningComputer Vision
  • 下單後立即進貨 (約3~4週)

相關主題

商品描述

Key Features

  • Build real-world Computer Vision applications using the power of neural networks
  • Implement image classification, object detection, and face recognition
  • Know best practices on effectively building and deploying deep learning models in Java

Book Description

Although machine learning is an exciting world to explore, you may feel confused by all of its theoretical aspects. As a Java developer, you will be used to telling the computer exactly what to do, instead of being shown how data is generated; this causes many developers to struggle to adapt to machine learning.

The goal of this book is to walk you through the process of efficiently training machine learning and deep learning models for Computer Vision using the most up-to-date techniques. The book is designed to familiarize you with neural networks, enabling you to train them efficiently, customize existing state-of-the-art architectures, build real-world Java applications, and get great results in a short space of time. You will build real-world Computer Vision applications, ranging from a simple Java handwritten digit recognition model to real-time Java autonomous car driving systems and face recognition models.

By the end of this book, you will have mastered the best practices and modern techniques needed to build advanced Computer Vision Java applications and achieve production-grade accuracy.

What you will learn

  • Discover neural networks and their applications in Computer Vision
  • Explore the popular Java frameworks and libraries for deep learning
  • Build deep neural networks in Java
  • Implement an end-to-end image classification application in Java
  • Perform real-time video object detection using deep learning
  • Enhance performance and deploy applications for production

Who this book is for

This book is for data scientists, machine learning developers and deep learning practitioners with Java knowledge who want to implement machine learning and deep neural networks in the computer vision domain. You will need to have a basic knowledge of Java programming.

商品描述(中文翻譯)

主要特點


  • 利用神經網絡的強大功能構建真實世界的計算機視覺應用程式

  • 實現圖像分類、物體檢測和人臉識別

  • 了解在Java中有效構建和部署深度學習模型的最佳實踐

書籍描述

儘管機器學習是一個令人興奮的領域,但其中的理論方面可能會讓您感到困惑。作為一名Java開發人員,您習慣於告訴計算機確切要做什麼,而不是被展示數據是如何生成的;這使得許多開發人員難以適應機器學習。

本書的目標是引導您通過使用最新技術高效訓練計算機視覺的機器學習和深度學習模型的過程。本書旨在讓您熟悉神經網絡,使您能夠高效地訓練它們,自定義現有的最先進架構,構建真實世界的Java應用程式,並在短時間內獲得出色的結果。您將構建真實世界的計算機視覺應用程式,從簡單的Java手寫數字識別模型到實時Java自動駕駛系統和人臉識別模型。

通過閱讀本書,您將掌握構建高級計算機視覺Java應用程式所需的最佳實踐和現代技術,並實現生產級的準確性。

您將學到什麼


  • 了解神經網絡及其在計算機視覺中的應用

  • 探索用於深度學習的流行Java框架和庫

  • 在Java中構建深度神經網絡

  • 實現一個端到端的圖像分類應用程式

  • 使用深度學習進行實時視頻物體檢測

  • 提高性能並部署生產應用程式

適合閱讀對象

本書適合具有Java知識的數據科學家、機器學習開發人員和深度學習從業者,他們希望在計算機視覺領域實現機器學習和深度神經網絡。您需要具備基本的Java編程知識。

目錄大綱

  1. Introduction to Computer Vision and Training Neural Networks
  2. Convolutional Neural Network Architectures
  3. Transfer Learning and Deep CNN Architectures
  4. Real-Time Object Detection
  5. Creating Art with Neural Style Transfer
  6. Face Recognition

目錄大綱(中文翻譯)


  1. 計算機視覺和神經網絡訓練介紹

  2. 卷積神經網絡架構

  3. 遷移學習和深度卷積神經網絡架構

  4. 實時物體檢測

  5. 利用神經風格轉換創作藝術

  6. 人臉識別