Mastering New Age Computer Vision: Advanced techniques in computer vision object detection, segmentation, and deep learning (English Edition)
暫譯: 掌握新世代電腦視覺：電腦視覺物件偵測、分割與深度學習的進階技術（英文版）
Ralte, Zonunfeli
- 出版商: BPB Publications
- 出版日期: 2025-02-19
- 售價: $1,940
- 貴賓價: 9.5 折 $1,843
- 語言: 英文
- 頁數: 428
- 裝訂: Quality Paper - also called trade paper
- ISBN: 9365898404
- ISBN-13: 9789365898408
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相關分類:
DeepLearning、Computer Vision
海外代購書籍(需單獨結帳)
商品描述
DESCRIPTION
Mastering New Age Computer Vision is a comprehensive guide that explores the latest advancements in computer vision, a field that is enabling machines to not only see but also understand and interpret the visual world in increasingly sophisticated ways, guiding you from foundational concepts to practical applications.
This book explores cutting-edge computer vision techniques, starting with zero-shot and few-shot learning, DETR, and DINO for object detection. It covers advanced segmentation models like Segment Anything and Vision Transformers, along with YOLO and CLIP. Using PyTorch, readers will learn image regression, multi-task learning, multi-instance learning, and deep metric learning. Hands-on coding examples, dataset preparation, and optimization techniques help apply these methods in real-world scenarios. Each chapter tackles key challenges, introduces architectural innovations, and improves performance in object detection, segmentation, and vision-language tasks.
By the time you have turned the final page of this book, you will be a confident computer vision practitioner, armed with a comprehensive grasp of core principles and the ability to apply cutting-edge techniques to solve real-world problems. You will be prepared to develop innovative solutions across a broad spectrum of computer vision challenges, actively contributing to the ongoing advancements in this dynamic field.
WHAT YOU WILL LEARN
● Use PyTorch for both basic and advanced image processing.
● Build object detection models using CNNs and modern frameworks.
● Apply multi-task and multi-instance learning to complex datasets.
● Develop segmentation models, including panoptic segmentation.
● Improve feature representation with metric learning and bilinear pooling.
● Explore transformers and self-supervised learning for computer vision.
WHO THIS BOOK IS FOR
This book is for data scientists, AI practitioners, and researchers with a basic understanding of Python programming and ML concepts. Familiarity with deep learning frameworks like PyTorch and foundational knowledge of computer vision will help readers fully grasp the advanced techniques discussed.
商品描述(中文翻譯)
書籍描述
《掌握新時代計算機視覺》是一本全面的指南，探討計算機視覺的最新進展，這個領域使機器不僅能夠看見，還能理解和解釋視覺世界，以越來越複雜的方式引導您從基礎概念到實際應用。
本書探討尖端的計算機視覺技術，從零樣本學習（zero-shot learning）和少樣本學習（few-shot learning）、DETR 和 DINO 進行物體檢測開始。它涵蓋了先進的分割模型，如 Segment Anything 和 Vision Transformers，以及 YOLO 和 CLIP。讀者將使用 PyTorch 學習圖像回歸、多任務學習、多實例學習和深度度量學習。實作的程式碼範例、數據集準備和優化技術幫助將這些方法應用於現實世界的場景。每一章都針對關鍵挑戰，介紹架構創新，並改善物體檢測、分割和視覺-語言任務的性能。
當您翻到本書的最後一頁時，您將成為一位自信的計算機視覺實踐者，擁有對核心原則的全面理解，並能夠應用尖端技術來解決現實世界的問題。您將準備好在廣泛的計算機視覺挑戰中開發創新解決方案，積極貢獻於這個動態領域的持續進步。
您將學到什麼
● 使用 PyTorch 進行基本和高級圖像處理。
● 使用 CNN 和現代框架構建物體檢測模型。
● 將多任務和多實例學習應用於複雜數據集。
● 開發分割模型，包括全景分割（panoptic segmentation）。
● 通過度量學習和雙線性池化（bilinear pooling）改善特徵表示。
● 探索變壓器（transformers）和自我監督學習（self-supervised learning）在計算機視覺中的應用。
本書適合誰閱讀
本書適合數據科學家、人工智慧實踐者和對 Python 程式設計及機器學習（ML）概念有基本了解的研究人員。熟悉深度學習框架如 PyTorch 以及計算機視覺的基礎知識將幫助讀者充分掌握所討論的高級技術。
