| 書目名稱 | Handbook of Fingerprint Recognition | | 編輯 | Davide Maltoni,Dario Maio,Jianjiang Feng | | 視頻video | http://file.papertrans.cn/422/421327/421327.mp4 | | 概述 | Using the successful formula of previous editions, the book includes recent state-of-the-art techniques.Covers all the major topics, concepts and methods for fingerprint security systems.Contains help | | 圖書封面 |  | | 描述 | .With their distinctiveness and stability over time, fingerprints continue to be the most widely used anatomical characteristic in systems that automatically recognize a person‘s identity..This fully updated third edition provides in-depth coverage of the state-of-the-art in fingerprint recognition readers, feature extraction, and matching algorithms and applications. Deep learning (resurgence beginning around 2012) has been a game changer for artificial intelligence and, in particular, computer vision?and biometrics. Performance improvements (both recognition accuracy and speed) for most biometric modalities can be attributed to the use of deep neural networks along with availability of large training sets and powerful hardware. Fingerprint recognition has also been approached by deep learning, resulting in effective and efficient methods for automated recognition and for learning robust fixed-length representations. However, the tiny ridge details in fingerprints known as minutiae are still competitive with the powerful representations learned by huge neural networks trained on big data..Features & Benefits:.Reflects the progress made in automated techniques for fingerprint recog | | 出版日期 | Book 2022Latest edition | | 關(guān)鍵詞 | Performance; Classification; Fingerprint; Fingerprint Matching; Fingerprint Recognition; Fingerprint Sens | | 版次 | 3 | | doi | https://doi.org/10.1007/978-3-030-83624-5 | | isbn_softcover | 978-3-030-83626-9 | | isbn_ebook | 978-3-030-83624-5 | | copyright | Springer Nature Switzerland AG 2022 |
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