Article
Chemistry, Multidisciplinary
Li Jiang, Xianghuan Liu, Haixia Wang, Dongdong Zhao
Summary: In this study, we propose a dual-branch network-based recognition method for multimodal biometric recognition using finger vein (FV) and inner knuckle print (IKP). The method combines convolutional neural network, transfer learning, and triplet loss function to complete feature representation and achieves deep multilevel fusion of the two modalities' features.
APPLIED SCIENCES-BASEL
(2022)
Article
Computer Science, Information Systems
Ahmad S. Tarawneh, Ahmad B. Hassanat, Esra'a Alkafaween, Bayan Sarayrah, Sami Mnasri, Ghada A. Altarawneh, Malek Alrashidi, Mansoor Alghamdi, Abdullah Almuhaimeed
Summary: The study explores the extraction of deep features from FKP images using the VGG-19 deep learning model, and validates the effectiveness of these deep features in an FKP recognition system through experiments.
Article
Computer Science, Artificial Intelligence
Geetika Arora, Avantika Singh, Aditya Nigam, Kamlesh Tiwari, Hari Mohan Pandey
Summary: This paper addresses the problem of identification in FKP databases and proposes the FKPIndexNet technique, which generates index tables using similarity preserving hash codes to achieve high identification accuracy and low search time.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Javad Khodadoust, Miguel Angel Medina-Perez, Raill Monroy, Ali Mohammad Khodadoust, Seyed Saeid Mirkamali
Summary: Authentication systems are crucial in modern life, and multibiometric systems offer enhanced security and recognition accuracy by combining biometric features. Before designing a multibiometric system, factors such as the number of biometric modalities, system accuracy, and budget allocation need to be carefully considered.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
P. Jayapriya, K. Umamaheswari
Summary: This research proposes an effective feature optimization technique using the K-nearest neighbor algorithm and differential evolution for finger knuckle print-based authentication. Experimental results show improved classification accuracy with this method.
NEURAL COMPUTING & APPLICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Meixiang Zhao, Zhigang Jia, Yunfeng Cai, Xiao Chen, Dunwei Gong
Summary: A new general ridge regression model is proposed for extracting low-dimensional features from 2DPCA and its variations, and the face recognition methods are improved by weighting each principle component a scatter measure.
Article
Computer Science, Information Systems
Alaa Eleyan
Summary: This study investigates the impact of feature fusion on face recognition performance by fusing different feature descriptors. The results show that fused feature descriptors can significantly improve performance, especially when the training set is limited.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2023)
Article
Computer Science, Information Systems
I. Michael Revina, W. R. Sam Emmanuel
Summary: Facial expression recognition is a powerful tool for social communication, involving preprocessing, feature extraction, and classification stages, with performance of different FER techniques compared based on the number of expressions recognized and algorithm complexity.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2021)
Article
Mathematics, Interdisciplinary Applications
Minghua Wan, Mengting Ge, Tianming Zhan, Zhangjing Yang, Hao Zheng, Guowei Yang
Summary: A new and effective dimensional reduction method for face recognition, utilizing sparse graph embedding with fuzzy set for image classification, is proposed in the study. Experimental results demonstrate its superiority over other algorithms in various datasets.
Article
Computer Science, Information Systems
Ratanak Khoeun, Watcharaphong Yookwan, Ponlawat Chophuk, Annupan Rodtook, Krisana Chinnasarn
Summary: The effectiveness of existing facial expression recognition approaches is hindered by the use of facial masks during the Covid-19 outbreak. This study proposes a new method called Star-Like Particle Polygon Estimation (SLPPE) for extracting features from partially obscured facial images. By using SLPPE to extract probability-based feature vectors, the proposed method achieves higher accuracy (99.01%, 98.7%, and 94.62%) compared to common CNN approaches on CK+, FER2013, and RAF-DB datasets.
Article
Chemistry, Analytical
Dingzhong Feng, Shanyu He, Zihao Zhou, Ye Zhang
Summary: This paper proposes a novel feature extraction method called principal component local preservation projections (PCLPP) for finger vein recognition. The method combines principal component analysis (PCA) and locality preserving projections (LPP) to construct a projection matrix that preserves both global and local features of the image, thereby improving the accuracy of image recognition.
Article
Computer Science, Artificial Intelligence
Jianwu Wan, Yinjuan Chen, Bing Bai
Summary: The paper proposes a unified cost-sensitive framework for face recognition, which significantly reduces the overall misclassification loss of face recognition system and classification errors associated with high costs, as demonstrated by experimental results.
PATTERN RECOGNITION
(2021)
Article
Computer Science, Artificial Intelligence
Hadis Heidari, Abdolah Chalechale
Summary: This paper introduces a deep learning-based method for human authentication using hand dorsal characteristics, including fingernail and finger knuckle print. By utilizing a multimodal biometric scheme and a CNN model with AlexNet, the proposed system demonstrates efficiency, robustness, and reliability, making it suitable for various real-world applications.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Engineering, Electrical & Electronic
Weigang Wang, Jie Qin, Yunwei Zhang, Dashan Deng, Shujuan Yu, Yun Zhang, Yuanjian Liu
Summary: The face image recognition technology based on subspace learning has limitations, so we propose the TNNL model to address sample-specific corruptions and outliers, and experimental results demonstrate its effectiveness.
DIGITAL SIGNAL PROCESSING
(2021)
Article
Computer Science, Artificial Intelligence
Decheng Liu, Xinbo Gao, Chunlei Peng, Nannan Wang, Jie Li
Summary: The article explores learning interpretable representations for complex heterogeneous faces and proposes the HFIDR and M-HFIDR methods for cross-modality recognition and synthesis tasks, achieving efficiency in face recognition and synthesis.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2022)
Article
Computer Science, Information Systems
Yi Chen, Ming Yang, Xianqing Chen, Bin Liu, Hainan Wang, Shuihua Wang
MULTIMEDIA TOOLS AND APPLICATIONS
(2018)
Article
Computer Science, Information Systems
Yi Chen, Yin Zhang, Hui-Min Lu, Xian-Qing Chen, Jian-Wu Li, Shui-Hua Wang
MULTIMEDIA TOOLS AND APPLICATIONS
(2018)
Article
Computer Science, Information Systems
Yu-Dong Zhang, Xiao-Xia Hou, Yi Chen, Hong Chen, Ming Yang, Jiquan Yang, Shui-Hua Wang
MULTIMEDIA TOOLS AND APPLICATIONS
(2018)
Article
Computer Science, Information Systems
Shui-Hua Wang, Yi Chen
MULTIMEDIA TOOLS AND APPLICATIONS
(2020)
Article
Computer Science, Software Engineering
Shuihua Wang, Junding Sun, Irfan Mehmood, Chichun Pan, Yi Chen, Yu-Dong Zhang
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2020)
Article
Computer Science, Artificial Intelligence
Shenghua Gu, Yi Chen, Fangqing Sheng, Tianming Zhan, Yunjie Chen
MACHINE VISION AND APPLICATIONS
(2019)
Article
Computer Science, Artificial Intelligence
Zheng Zhang, Qi Zhu, Guo-Sen Xie, Yi Chen, Zhengming Li, Shuihua Wang
Article
Computer Science, Artificial Intelligence
Zhenyu Lu, Yanzhong Bai, Yi Chen, Chunqiu Su, Shanshan Lu, Tianming Zhan, Xunning Hong, Shuihua Wang
PATTERN RECOGNITION LETTERS
(2020)
Article
Computer Science, Artificial Intelligence
Shuaizhen Yao, Jianhua Tan, Yi Chen, Yanhui Gu
Summary: Recent research introduces a new medical image synthesis model, WFT-GAN, which improves the quality of generated medical images by adopting weighted feature transfer and local perceptual adversarial loss. This approach aims to avoid the negative impact of blurry and meaningless features on medical judgment, and has shown promising results in synthesizing higher-quality medical images across three different datasets.
MACHINE VISION AND APPLICATIONS
(2021)
Article
Engineering, Civil
Xiaohong Zhang, Yi Chen, Haofeng Zhang, Shuihua Wang, Jianfeng Lu, Jingyu Yang
Summary: In this paper, we propose a Mutual Encouragement Network (MENet) that simultaneously achieves semantic segmentation and depth estimation, and outperforms existing methods in experiments.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Heng Tao Shen, Xiaofeng Zhu, Zheng Zhang, Shui-Hua Wang, Yi Chen, Xing Xu, Jie Shao
Summary: A novel sparse regression method is proposed in this paper to fuse auxiliary data into predictor data for pMCI/sMCI classification in AD research. This method addresses the challenge of identifying differences between pMCI and sMCI subjects, while also handling outliers and age effects in the data.
INFORMATION FUSION
(2021)
Article
Engineering, Civil
Xiaohong Zhang, Yi Chen, Ziyi Shen, Yuming Shen, Haofeng Zhang, Yudong Zhang
Summary: This work proposes a novel multi-level unsupervised domain adaptation (UDA) model named Confidenceand-Refinement Adaptation Model (CRAM), which alleviates the domain discrepancy through a confidence-aware entropy alignment (CEA) module and a style feature alignment (SFA) module. Experiments show that CRAM achieves comparable performance with advantages in simplicity and convergence speed on two challenging benchmarks.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Jingren Liu, Yi Chen, Huajun Liu, Haofeng Zhang, Yudong Zhang
Summary: Object detection is one of the most important tasks for environment perception in intelligent transportation systems. Most existing research focuses on the fully supervised scenario, which can lead to model failure. Zero-shot learning models have the ability to detect unseen objects. However, generative models generally perform better than visual-semantic mapping methods in Generalized Zero-Shot Detection (GZSD). In order to overcome this limitation in generative methods, we propose using curriculum learning to generate more precise unseen visual features. Our method shows superior performance compared to state-of-the-art methods.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Computer Science, Information Systems
Yinxia Sun, Pushpita Chatterjee, Yi Chen, Yudong Zhang
Summary: The Internet of Things (IoT) has brought convenience and intelligence to our lives, but it also raises serious security concerns, especially regarding data privacy. Encryption is an effective method to protect data privacy in IoT, and identity-based public-key encryption (IBE) is widely used due to its efficiency and convenience. However, the revocation of a user whose private key may have been exposed is a challenge in IBE. In this article, an efficient and practical IBE scheme with revocation functionality is proposed to preserve data privacy in IoT applications.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Artificial Intelligence
Jianjian Yin, Zhichao Zheng, Yulu Pan, Yanhui Gu, Yi Chen
Summary: Semi-supervised semantic segmentation aims to classify pixels using both labeled and unlabeled images. The utilization of unlabeled images is crucial in semi-supervised learning. Existing methods tend to focus on reliable pixels while ignoring unreliable pixels, resulting in information loss. Uneven distribution of pixels per category can also lead to misclassification.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
