Deep Learning in Biometrics

Deep Learning is now synonymous with applied machine learning. Many technology giants (e.g. Google, Microsoft, Apple, IBM) as well as start-ups are focusing on deep learning-based techniques for data analytics and artificial intelligence. This technology applies quite strongly to biometrics. This book covers topics in deep learning, namely convolutional neural networks, deep belief network and stacked autoencoders. The focus is also on the application of these techniques to various biometric modalities: face, iris, palmprint, and fingerprints, while examining the future trends in deep learning and biometric research.

深度學習現在已經成為應用機器學習的代名詞。許多科技巨頭（例如Google、Microsoft、Apple、IBM）以及初創公司都專注於基於深度學習的數據分析和人工智慧技術。這項技術在生物特徵識別方面具有很強的應用性。本書涵蓋了深度學習的主題，包括卷積神經網絡、深度置信網絡和堆疊自編碼器。同時，重點還放在這些技術在各種生物特徵識別模式（如臉部、虹膜、掌紋和指紋）上的應用，同時探討深度學習和生物特徵識別研究的未來趨勢。