Deep Learning in Visual Computing: Explanations and Examples

Ugail, Hassan

  • 出版商: CRC
  • 出版日期: 2022-07-07
  • 售價: $2,710
  • 貴賓價: 9.5$2,575
  • 語言: 英文
  • 頁數: 134
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 036754962X
  • ISBN-13: 9780367549626
  • 相關分類: DeepLearning
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Deep learning is an artificially intelligent entity that teaches itself and can be utilized to make predictions. Deep learning mimics the human brain and provides learned solutions addressing many challenging problems in the area of visual computing. From object recognition to image classification for diagnostics, deep learning has shown the power of artificial deep neural networks in solving real world visual computing problems with super-human accuracy. The introduction of deep learning into the field of visual computing has meant to be the death of most of the traditional image processing and computer vision techniques. Today, deep learning is considered to be the most powerful, accurate, efficient and effective method with the potential to solve many of the most challenging problems in visual computing.

This book provides an insight into deep machine learning and the challenges in visual computing to tackle the novel method of machine learning. It introduces readers to the world of deep neural network architectures with easy-to-understand explanations. From face recognition to image classification for diagnosis of cancer, the book provides unique examples of solved problems in applied visual computing using deep learning. Interested and enthusiastic readers of modern machine learning methods will find this book easy to follow. They will find it a handy guide for designing and implementing their own projects in the field of visual computing.





Prof Hassan Ugail is Director of the Centre for Visual Computing at the University of Bradford, UK. He is a renowned computer scientist in the area of visual computing and artificial intelligence (AI). He is an advocate of AI for helping to tackle real world issues in the areas of digital health, innovative engineering and sustainable societies in general. More specifically, he works in the area of human biometrics especially the development of cutting-edge AI solutions for biometric face recognition. His most recent work in this area includes helping to unravel the real identity of the two Russian spies at the heart of the Salisbury Novichok poisoning case - one of the biggest international stories of 2018.


Prof Hassan Ugail是英國布拉德福德大學視覺計算中心的主任。他是視覺計算和人工智慧領域的知名計算機科學家。他主張利用人工智慧來解決數字健康、創新工程和可持續社會等實際問題。更具體地說,他在人體生物特徵識別方面進行研究,尤其是開發尖端的人工智慧解決方案用於生物特徵臉部識別。他最近在這個領域的工作包括幫助揭示薩利斯伯里諾維奇中毒案核心的兩名俄羅斯間諜的真實身份,這是2018年最重要的國際新聞之一。