標題: Titlebook: Handbook of Face Recognition; Stan Z. Li,Anil K. Jain,Jiankang Deng Book 2024Latest edition The Editor(s) (if applicable) and The Author(s [打印本頁] 作者: 教條 時間: 2025-3-21 17:59
書目名稱Handbook of Face Recognition影響因子(影響力)
書目名稱Handbook of Face Recognition影響因子(影響力)學科排名
書目名稱Handbook of Face Recognition網絡公開度
書目名稱Handbook of Face Recognition網絡公開度學科排名
書目名稱Handbook of Face Recognition被引頻次
書目名稱Handbook of Face Recognition被引頻次學科排名
書目名稱Handbook of Face Recognition年度引用
書目名稱Handbook of Face Recognition年度引用學科排名
書目名稱Handbook of Face Recognition讀者反饋
書目名稱Handbook of Face Recognition讀者反饋學科排名
作者: 著名 時間: 2025-3-21 20:22
https://doi.org/10.1007/978-3-662-29459-8comes the most popular deep neural network model to process visual data, including images and videos. Until now, a lot of modern fundamental computer vision systems, e.g., image classification and face recognition, are usually built upon convolutional networks.作者: Synthesize 時間: 2025-3-22 01:48
Zerkleinerungs-Vorrichtungen und Mahlanlagenmodels to design generative models for facial images. However, the abstraction and distortion of predefined models hinder the realism of the generated faces. With the development of deep learning, a large number of generative models have been proposed, especially in the field of face image generatio作者: 諄諄教誨 時間: 2025-3-22 08:19 作者: aquatic 時間: 2025-3-22 11:32
https://doi.org/10.1007/978-3-658-14222-3ted facial attribute analysis has become an active field in the area of biometric recognition due to its wide range of possible applications, such as face verification?[., .], face identification?[., .], or surveillance?[.], just to mention a few.作者: locus-ceruleus 時間: 2025-3-22 14:21 作者: Cholagogue 時間: 2025-3-22 17:55 作者: NADIR 時間: 2025-3-23 00:27
https://doi.org/10.1007/979-8-8688-0105-1tion?[., ., .], matching faces across ages?[., ., ., .], across modalities?[., ., ., ., .], and occlusions?[., ., .]. Among these progresses, not only the very deep neural networks?[., ., ., .] and sophisticated design of loss functions?[., ., ., ., .], but also large-scale training datasets?[., ., 作者: VEIL 時間: 2025-3-23 03:50 作者: Barter 時間: 2025-3-23 07:16 作者: 凝視 時間: 2025-3-23 13:31
https://doi.org/10.1007/978-3-663-05163-3tworks (DNNs) [18, 37, 39]. Empowered by the excellent performance of DNNs, face recognition models are widely deployed in various safety-critical scenarios ranging from finance/payment to automated surveillance systems. Despite its booming development, recent research in adversarial machine learnin作者: 吞噬 時間: 2025-3-23 14:35 作者: 荒唐 時間: 2025-3-23 21:23 作者: corpus-callosum 時間: 2025-3-24 01:41
Face Recognition Research and Developmenth topics in computer vision with great commercial applications?[., ., ., .], like biometric authentication, financial security, access control, intelligent surveillance, etc. Because of its commercial potential and practical value, face recognition has attracted great interest from both academia and作者: Allergic 時間: 2025-3-24 02:42
Convolutional Neural Networks and Architecturescomes the most popular deep neural network model to process visual data, including images and videos. Until now, a lot of modern fundamental computer vision systems, e.g., image classification and face recognition, are usually built upon convolutional networks.作者: 漂白 時間: 2025-3-24 08:56
Generative Networksmodels to design generative models for facial images. However, the abstraction and distortion of predefined models hinder the realism of the generated faces. With the development of deep learning, a large number of generative models have been proposed, especially in the field of face image generatio作者: 秘密會議 時間: 2025-3-24 13:46 作者: ANA 時間: 2025-3-24 18:07
Facial Attribute Analysisted facial attribute analysis has become an active field in the area of biometric recognition due to its wide range of possible applications, such as face verification?[., .], face identification?[., .], or surveillance?[.], just to mention a few.作者: 嘮叨 時間: 2025-3-24 22:14
Face Feature Embeddingty. To implement face verification and recognition at scale, it is indispensable to have a discriminative face embedding in which faces of the same person have small distances and faces of different people have large distances. Once such embedding is obtained, face verification involves thresholding作者: 裝勇敢地做 時間: 2025-3-25 01:15
Video-Based Face Recognitioncontent analysis, etc. Compared to still face recognition, video-based face recognition is more challenging due to a much larger amount of data to be processed and significant intra/inter-class variations caused by motion blur, low video quality, occlusion, frequent scene changes, and unconstrained 作者: 抑制 時間: 2025-3-25 05:34 作者: 十字架 時間: 2025-3-25 10:57 作者: gout109 時間: 2025-3-25 13:01
Reducing Bias in Face RecognitionFR performance. The goal of this research is to learn a fair face representation, where the faces of every group could be equally well-represented. Specifically, we explore de-biasing approaches by designing two different network architectures using deep learning. Meanwhile, we evaluate the model’s 作者: 貞潔 時間: 2025-3-25 15:57 作者: 集聚成團 時間: 2025-3-25 23:21
Heterogeneous Face Recognition identity verification in uncontrolled scenarios. With the development of deep learning models in image processing, superior recognition accuracy has been achieved recently [., .]. However, real face images are captured through different sources, such as sketch artists and infrared imaging devices, 作者: obstinate 時間: 2025-3-26 01:02 作者: Neonatal 時間: 2025-3-26 06:50 作者: 到婚嫁年齡 時間: 2025-3-26 10:35 作者: Grievance 時間: 2025-3-26 12:39
on, tracking, alignment, feature extraction.Describes a broa.The history of computer-aided face recognition dates to the 1960s, yet the problem of automatic face recognition – a task that humans perform routinely and effortlessly in our daily lives – still poses great challenges, especially in uncon作者: 角斗士 時間: 2025-3-26 17:47 作者: intertwine 時間: 2025-3-26 21:02
https://doi.org/10.1007/978-981-99-3072-2ecifically, we explore de-biasing approaches by designing two different network architectures using deep learning. Meanwhile, we evaluate the model’s demographic bias on various datasets to show how much bias is mitigated in our attempt at improving the fairness of face representations extracted from CNNs.作者: 火車車輪 時間: 2025-3-27 04:45 作者: 狗窩 時間: 2025-3-27 07:30
https://doi.org/10.1007/978-3-642-73638-4been achieved recently [., .]. However, real face images are captured through different sources, such as sketch artists and infrared imaging devices, called .. Furthermore, matching face images in different modalities, which is referred to as ., is now attracting growing attention in both biometrics research and industry.作者: 制度 時間: 2025-3-27 11:20
Book 2024Latest editionly and effortlessly in our daily lives – still poses great challenges, especially in unconstrained conditions..This highly anticipated new edition provides a comprehensive account of face recognition research and technology, spanning the full range of topics needed for designing operational recognit作者: EVEN 時間: 2025-3-27 16:17 作者: Jacket 時間: 2025-3-27 19:32 作者: 輕浮思想 時間: 2025-3-28 00:51 作者: 澄清 時間: 2025-3-28 05:09 作者: Grandstand 時間: 2025-3-28 07:32 作者: CLAMP 時間: 2025-3-28 12:03
Facial Landmark Localizationtions and face region contours, which is essential for many face analysis tasks, e.g., recognition, animation, attributes classification, and face editing. These applications usually run on lightweight devices in uncontrolled environments, requiring landmark detectors to be accurate, robust, and computationally efficient, all at the same time.作者: Infect 時間: 2025-3-28 16:03 作者: exquisite 時間: 2025-3-28 19:26 作者: 改變 時間: 2025-3-29 00:48 作者: Chandelier 時間: 2025-3-29 03:08 作者: Individual 時間: 2025-3-29 08:17 作者: 他日關稅重重 時間: 2025-3-29 11:28
https://doi.org/10.1007/978-94-6209-452-9Face recognition technology has been widely used in daily interactive applications such as checking-in and mobile payment due to its convenience and high accuracy. However, its vulnerability to presentation attacks (PAs) limits its reliable use in ultra-secure application scenarios.作者: nephritis 時間: 2025-3-29 15:46 作者: 樹膠 時間: 2025-3-29 23:47 作者: 整潔漂亮 時間: 2025-3-30 01:59
978-3-031-43569-0The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl作者: 連系 時間: 2025-3-30 07:25 作者: 想象 時間: 2025-3-30 11:19 作者: 除草劑 時間: 2025-3-30 15:53