Robust gait recognition: a comprehensive survey

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Silhouette analysis-based gait recognition for human identification

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General Tensor Discriminant Analysis and Gabor Features for Gait Recognition

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The humanID gait challenge problem: data sets, performance, and analysis

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A Framework for Evaluating the Effect of View Angle, Clothing and Carrying Condition on Gait Recognition

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MPCA: Multilinear Principal Component Analysis of Tensor Objects

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A Comprehensive Study on Cross-View Gait Based Human Identification with Deep CNNs

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Gait analysis for recognition and classification

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Identification of Humans Using Gait

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Deep Gait Recognition: A Survey

Sepas‐Moghaddam, A., & Etemad, A. (2022) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2022.3151865 · Cited by 344

Deep Learning-Based Gait Recognition Using Smartphones in the Wild

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Gait Recognition Based on Deep Learning: A Survey

Filipi Gonçalves dos Santos, C., Oliveira, D. D. S., A. Passos, L., Gonçalves Pires, R., Felipe Silva Santos, D., Pascotti Valem, L., P. Moreira, T., Cleison S. Santana, M., Roder, M., Paulo Papa, J., et al. (2023) · ACM Computing Surveys · doi:10.1145/3490235 · Cited by 108

A Comprehensive Survey on Deep Gait Recognition: Algorithms, Datasets, and Challenges

Shen, C., Yu, S., Wang, J., Huang, G. Q., & Wang, L. (2024) · IEEE Transactions on Biometrics Behavior and Identity Science · doi:10.1109/tbiom.2024.3486345 · Cited by 112

Spatial transformer network on skeleton‐based gait recognition

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Using Siamese Neural Networks to Perform Cross-System Behavioral Authentication in Virtual Reality

Miller, R. A., Banerjee, N. K., & Banerjee, S. (2021) · IEEE Conference on Virtual Reality and 3D User Interfaces (VR) · doi:10.1109/vr50410.2021.00035 · Cited by 75

Data preprocessing and feature selection techniques in gait recognition: A comparative study of machine learning and deep learning approaches

Parashar, A., Parashar, A., Ding, W., Shabaz, M., & Rida, I. (2023) · Pattern Recognition Letters · doi:10.1016/j.patrec.2023.05.021 · Cited by 72

A comprehensive overview of feature representation for biometric recognition

Rida, I., Almaadeed, N., Al-Maadeed, S. A., & Bakshi, S. (2018) · Multimedia Tools and Applications · doi:10.1007/s11042-018-6808-5 · Cited by 72

View-Invariant Gait Recognition With Attentive Recurrent Learning of Partial Representations

Sepas‐Moghaddam, A., & Etemad, A. (2020) · IEEE Transactions on Biometrics Behavior and Identity Science · doi:10.1109/tbiom.2020.3031470 · Cited by 66

Identifying the Main Risk Factors for Cardiovascular Diseases Prediction Using Machine Learning Algorithms

Guarneros-Nolasco, L. R., Cruz-Ramos, N. A., Alor‐Hernández, G., Rodríguez-Mazahua, L., & Sánchez-Cervantes, J. L. (2021) · Mathematics · doi:10.3390/math9202537 · Cited by 65

CMOS Image Sensors in Surveillance System Applications

Sukhavasi, S. B., Sukhavasi, S. B., Elleithy, K. M., Abuzneid, A., & Elleithy, A. (2021) · Sensors · doi:10.3390/s21020488 · Cited by 57

Robust Gait Recognition Based on Deep CNNs With Camera and Radar Sensor Fusion

Shi, Y., Du, L., Chen, X., Liao, X., Yu, Z., Li, Z., Wang, C., & Xue, S. (2023) · IEEE Internet of Things Journal · doi:10.1109/jiot.2023.3242417 · Cited by 48

Gait Recognition via Deep Learning of the Center-of-Pressure Trajectory

Terrier, P. (2020) · Applied Sciences · doi:10.3390/app10030774 · Cited by 47

Monitoring Indoor People Presence in Buildings Using Low-Cost Infrared Sensor Array in Doorways

Perra, C., Kumar, A., Losito, M., Pirino, P., Moradpour, M., & Gatto, G. (2021) · Sensors · doi:10.3390/s21124062 · Cited by 45

Intra-class variations with deep learning-based gait analysis: A comprehensive survey of covariates and methods

Parashar, A., Shekhawat, R. S., Ding, W., & Rida, I. (2022) · Neurocomputing · doi:10.1016/j.neucom.2022.07.002 · Cited by 46

Real-time gait biometrics for surveillance applications: A review

Parashar, A., Parashar, A., Abate, A. F., Shekhawat, R. S., & Rida, I. (2023) · Image and Vision Computing · doi:10.1016/j.imavis.2023.104784 · Cited by 43

Human centric attention with deep multiscale feature fusion framework for activity recognition in Internet of Medical Things

Hussain, A., Khan, S. U., Rida, I., Khan, N., & Baik, S. W. (2023) · Information Fusion · doi:10.1016/j.inffus.2023.102211 · Cited by 44

Hierarchical Spatio-Temporal Representation Learning for Gait Recognition

Wang, L., Лю, Б., Liang, F., & Wang, B. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.01799 · Cited by 43

Vision-based approaches towards person identification using gait

Khan, M. H., Farid, M. S., & Grzegorzek, M. (2021) · Computer Science Review · doi:10.1016/j.cosrev.2021.100432 · Cited by 40

Person Recognition Based on Deep Gait: A Survey

Khaliluzzaman, M., Uddin, A., Deb, K., & Hasan, M. J. (2023) · Sensors · doi:10.3390/s23104875 · Cited by 35

Gait recognition invariant to carried objects using alpha blending generative adversarial networks

Li, X., Makihara, Y., Xu, C., Yagi, Y., & Ren, M. (2020) · Pattern Recognition · doi:10.1016/j.patcog.2020.107376 · Cited by 35

View-Independent Gait Recognition Using Joint Replacement Coordinates (JRCs) and Convolutional Neural Network

Limcharoen, P., Khamsemanan, N., & Nattee, C. (2020) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2020.2985535 · Cited by 34

A binary dandelion algorithm using seeding and chaos population strategies for feature selection

Zhao, Y., Dong, J., Li, X., Chen, H., & Li, S. (2022) · Applied Soft Computing · doi:10.1016/j.asoc.2022.109166 · Cited by 35

Gait Recognition using Multi-Scale Partial Representation Transformation with Capsules

Sepas‐Moghaddam, A., Ghorbani, S., Troje, N. F., & Etemad, A. (2021) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr48806.2021.9412517 · Cited by 33

Using a Skeleton Gait Energy Image for Pathological Gait Classification

Loureiro, J., & Correia, P. L. (2020) · International Conference on Automatic Face and Gesture Recognition · doi:10.1109/fg47880.2020.00064 · Cited by 33

Triple-Type Feature Extraction for Palmprint Recognition

Wu, L., Xu, Y. D., Cui, Z., Zuo, Y., Zhao, S., & Fei, L. (2021) · Sensors · doi:10.3390/s21144896 · Cited by 30

Collaborative Feature Learning for Gait Recognition Under Cloth Changes

Yao, L., Kusakunniran, W., Wu, Q., Xu, J., & Zhang, J. (2021) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2021.3112564 · Cited by 27

Advancements in artificial intelligence for biometrics: A deep dive into model-based gait recognition techniques

Parashar, A., Parashar, A., Shabaz, M., Gupta, D., Sahu, A. K., & Khan, M. A. (2023) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2023.107712 · Cited by 31

Gait Learning Based Authentication for Intelligent Things

Zhang, H., Liu, J., Li, K., Tan, H., & Wang, G. (2020) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2020.2977418 · Cited by 26

Estimation of tea quality grade using statistical identification of key variables

Li, M., Pan, T., & Chen, Q. (2020) · Food Control · doi:10.1016/j.foodcont.2020.107485 · Cited by 26

Automated Simulation Framework for Urban Wind Environments Based on Aerial Point Clouds and Deep Learning

Sun, C., Zhang, F., Zhao, P., Zhao, X., Huang, Y., & Lu, X. (2021) · Remote Sensing · doi:10.3390/rs13122383 · Cited by 25

A multi-view human gait recognition using hybrid whale and gray wolf optimization algorithm with a random forest classifier

Rao, P. S., Parida, P., Sahu, G., & Dash, S. (2023) · Image and Vision Computing · doi:10.1016/j.imavis.2023.104721 · Cited by 23

Gait Recognition and Re-Identification Based on Regional LSTM for 2-Second Walks

Limcharoen, P., Khamsemanan, N., & Nattee, C. (2021) · IEEE Access · doi:10.1109/access.2021.3102936 · Cited by 23

GaitParsing: Human Semantic Parsing for Gait Recognition

Wang, Z., Hou, S., Zhang, M., Liu, X., Cao, C., & Huang, Y. (2023) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2023.3325962 · Cited by 21

Intelligent recognition system for viewpoint variations on gait and speech using CNN-CapsNet

Linda, G. M., Lakshmi, N. V. S. S. R., Murugan, N. S., Mahapatra, R. P., Muthukumaran, V., & Sivaram, M. (2021) · International Journal of Intelligent Computing and Cybernetics · doi:10.1108/ijicc-08-2021-0178 · Cited by 18

Pathological-Gait Recognition Using Spatiotemporal Graph Convolutional Networks and Attention Model

Kim, J., Seo, H., Naseem, M. T., & Lee, C.-S. (2022) · Sensors · doi:10.3390/s22134863 · Cited by 16

Smart Gravimetric System for Enhanced Security of Accesses to Public Places Embedding a MobileNet Neural Network Classifier

Addabbo, T., Fort, A., Mugnaini, M., Vignoli, V., Intravaia, M., Tani, M., Bianchini, M., Scarselli, F., & Corradini, B. T. (2022) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2022.3162270 · Cited by 15

Utilizing Spatio Temporal Gait Pattern and Quadratic SVM for Gait Recognition

Masood, H., & Farooq, H. (2022) · Electronics · doi:10.3390/electronics11152386 · Cited by 15

LandmarkGait: Intrinsic Human Parsing for Gait Recognition

Wang, Z., Hou, S., Zhang, M., Liu, X., Cao, C., Huang, Y., & Xu, S. (2023) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3581783.3611840 · Cited by 15

Walk as you feel: Privacy preserving emotion recognition from gait patterns

Bisogni, C., Cimmino, L., Nappi, M., Pannese, T., & Pero, C. (2023) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2023.107565 · Cited by 15

Improving Gait Recognition Through Occlusion Detection and Silhouette Sequence Reconstruction

Hasan, K., Uddin, M. Z., Ray, A., Hasan, M., Alnajjar, F. S. K., & Ahad, M. A. R. (2024) · IEEE Access · doi:10.1109/access.2024.3482430 · Cited by 15

Generalized Inter-class Loss for Gait Recognition

Yu, W., Yu, H., Huang, Y., & Wang, L. (2022) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3503161.3548311 · Cited by 15

RF‐Gait: Gait‐Based Person Identification with COTS RFID

Jiang, S., Jiang, J., Wang, S., Zhang, Y., Feng, Y. X., Cao, Z., & Liu, Y. (2022) · Wireless Communications and Mobile Computing · doi:10.1155/2022/3638436 · Cited by 13

A survey on gait recognition against occlusion: taxonomy, dataset and methodology

Li, T., Ma, W., Zheng, Y., Fan, X., Yang, G., Wang, L., & Li, Z. (2024) · PeerJ Computer Science · doi:10.7717/peerj-cs.2602 · Cited by 16

A real-time multi view gait-based automatic gender classification system using kinect sensor

Azhar, M. H., Ullah, S., Raees, M. A., Rahman, K. U., & Rehman, I. U. (2022) · Multimedia Tools and Applications · doi:10.1007/s11042-022-13704-3 · Cited by 13

VersatileGait: A Large-Scale Synthetic Gait Dataset with Fine-GrainedAttributes and Complicated ScenariosPreprint

Dou, H., Zhang, W., Zhang, P., Zhao, Y., Li, S., Qin, Z., Wu, F., Dong, L., & Li, X. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2101.01394 · Cited by 13

A robust similarity based deep siamese convolutional neural network for gait recognition across views

George, M. L., Govindarajan, T., Rajasekaran, K. A., & Bandi, S. R. (2020) · Computational Intelligence · doi:10.1111/coin.12361 · Cited by 12

A Large-Scale Synthetic Gait Dataset Towards in-the-Wild Simulation and Comparison Study

Zhang, P., Dou, H., Zhang, W., Zhao, Y., Qin, Z., Hu, D., Fang, Y., & Li, X. (2022) · ACM Transactions on Multimedia Computing Communications and Applications · doi:10.1145/3517199 · Cited by 12

Forensic shoe-print identification: a brief surveyPreprint

Rida, I., Fei, L., Proença, H. P. M. C., Nait-Ali, A., & Hadid, A. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1901.01431 · Cited by 23

Gait coordination feature modeling and multi-scale gait representation for gait recognition

Zhu, D., Ji, L., Zhu, L., & Li, C. (2024) · International Journal of Machine Learning and Cybernetics · doi:10.1007/s13042-024-02120-8 · Cited by 11

FCML-gait: fog computing and machine learning inspired human identity and gender recognition using gait sequences

Ahmed, K., & Saini, M. (2022) · Signal Image and Video Processing · doi:10.1007/s11760-022-02217-z · Cited by 11

Online Handwritten Signature Verification and Recognition Based on Dual-Tree Complex Wavelet Packet Transform

Foroozandeh, A., Hemmat, A. A., & Rabbani, H. (2020) · Journal of Medical Signals & Sensors · doi:10.4103/jmss.jmss_44_19 · Cited by 11

Gait Recognition Based on Two-Stream CNNs With Multisensor Progressive Feature Fusion

Qin, L., Guo, M., Zhou, K., Sun, J., Chen, X., & Qiu, J. (2024) · IEEE Sensors Journal · doi:10.1109/jsen.2024.3373100 · Cited by 10

A Novel Target-Aware Dual Matching and Compensatory Segmentation Tracker for Aerial Videos

Sun, R., Fang, L., Gao, X., & Gao, J. (2021) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2021.3109722 · Cited by 10

An Improved Behavioral Biometric System based on Gait and ECG signals

Mohamed-Boudiaf, U. D. S. E. D. L. T., Guelta, B., Tlemsani, R., Chouraqui, S., Mohamed-Boudiaf, U. D. S. E. D. L. T., & Benouis, M. (2019) · International journal of intelligent engineering and systems · doi:10.22266/ijies2019.1231.14 · Cited by 9

Towards Human Body-Part Learning for Model-Free Gait RecognitionPreprint

Rida, I. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1904.01620 · Cited by 9

A General Grid-Less Design Method for Location and Pressure Sensors with High Precision

Zhu, X., Cheng, X., Zhang, W., Gao, J., Dai, Y., & Gu, W. (2020) · Sensors · doi:10.3390/s20247286 · Cited by 8

Learning view‐invariant features using stacked autoencoder for skeleton‐based gait recognition

Hasan, M. M., & Mustafa, H. A. (2021) · IET Computer Vision · doi:10.1049/cvi2.12050 · Cited by 8

Protection of gait data set for preserving its privacy in deep learning pipeline

Parashar, A., & Shekhawat, R. S. (2022) · IET Biometrics · doi:10.1049/bme2.12093 · Cited by 8

HotFoot: Foot-Based User Identification Using Thermal Imaging

Saad, A., Izadi, K., Khan, A. A., Knierim, P., Schneegaß, S., Alt, F., & Abdelrahman, Y. (2023) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3580924 · Cited by 7

Geometric Deep Neural Network Using Rigid and Non-rigid Transformations for Landmark-based Human Behavior Analysis

Friji, R., Chaieb, F., Drira, H., & Kurtek, S. (2023) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2023.3291663 · Cited by 7

An Appearance Invariant Gait Recognition Technique Using Dynamic Gait Features

Masood, H., & Farooq, H. (2021) · International Journal of Optics · doi:10.1155/2021/5591728 · Cited by 7

GAITMM: Multi-Granularity Motion Sequence Learning for Gait Recognition

Wang, L., Лю, Б., Wang, B., & Yu, F. (2023) · Proceedings - International Conference on Image Processing · doi:10.1109/icip49359.2023.10221893 · Cited by 6

Autoencoder-guided GAN for minority-class cloth-changing gait data generation

Xu, J., Hai, L., & Hou, S. (2022) · Digital Signal Processing · doi:10.1016/j.dsp.2022.103608 · Cited by 6

A robust covariate‐invariant gait recognition based on pose features

Parashar, A., Parashar, A., & Shekhawat, R. S. (2022) · IET Biometrics · doi:10.1049/bme2.12103 · Cited by 6

Upper extremity kinematics: development of a quantitative measure of impairment severity and dissimilarity after stroke

Zaidi, K. F., & Harris-Love, M. L. (2023) · PeerJ · doi:10.7717/peerj.16374 · Cited by 6

Journey into gait biometrics: Integrating deep learning for enhanced pattern recognition

Parashar, A., Parashar, A., & Rida, I. (2024) · Digital Signal Processing · doi:10.1016/j.dsp.2024.104393 · Cited by 9

The Analysis of Electronic Circuit Fault Diagnosis Based on Neural Network Data Fusion Algorithm

Wang, N. (2020) · Symmetry · doi:10.3390/sym12030458 · Cited by 6

GLDH: Toward more efficient global low-density locality-sensitive hashing for high dimensions

Li, Y., Xiao, R., Wei, X., Liu, H., Shi, Z., & Du, . (2020) · Information Sciences · doi:10.1016/j.ins.2020.04.046 · Cited by 6

Graph-optimized coupled discriminant projections for cross-view gait recognition

Xu, W. (2021) · Applied Intelligence · doi:10.1007/s10489-021-02322-5 · Cited by 6

Person Identification Based on Static Features Extracted from Kinect Skeleton Data

Zhao, W., Yang, S., Qiu, T., & Luo, X. (2021) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/smc52423.2021.9659013 · Cited by 6

Key-Frame-Aware Hierarchical Learning for Robust Gait Recognition

Wang, K., & Huo, H. (2025) · Journal of Imaging · doi:10.3390/jimaging11110402 · Cited by 5

A Lightweight Pathological Gait Recognition Approach Based on a New Gait Template in Side-View and Improved Attention Mechanism

Li, C., Wang, B., Li, Y., & Liu, B. (2024) · Sensors · doi:10.3390/s24175574 · Cited by 7

Does My Gait Look Nice? Human Perception-Based Gait Relative Attribute Estimation Using Dense Trajectory Analysis

Shehata, A., Hayashi, Y., Makihara, Y., Muramatsu, D., & Yagi, Y. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-41299-9_8 · Cited by 5

A Data-Driven Interpretable Method Based on Reversely Built FIS and Its Applications in Measurement

Qu, F., Liu, J., Zhu, H., & Zhang, H. (2021) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2021.3055845 · Cited by 5

MMF-Gait: A Multi-Model Fusion-Enhanced Gait Recognition Framework Integrating Convolutional and Attention Networks

Hasan, K., Tuhin, K. A., Bapary, M. R. I., Doula, M. S. U., Alam, M. A., Ahad, M. A. R., & Uddin, M. Z. (2025) · Symmetry · doi:10.3390/sym17071155 · Cited by 5

Gait biometrics: investigating the use of the lower inner regions for people identification from landmark frames

Bekhouch, A., Bouchrika, I., & Doghmane, N. (2020) · IET Biometrics · doi:10.1049/iet-bmt.2020.0001 · Cited by 4

Vision-based gait analysis to detect Parkinson’s disease using hybrid Harris hawks and Arithmetic optimization algorithm with Random Forest classifier

Palla, S. R., Parida, P., & Sahu, G. (2024) · International Journal of Systems Assurance Engineering and Management · doi:10.1007/s13198-024-02508-3 · Cited by 4

Comparison of machine learning methods for the construction of a standalone gait diagnosis device

Han, Y., Wong, K. I., & Murray, I. D. (2020) · IET Signal Processing · doi:10.1049/iet-spr.2019.0228 · Cited by 4

A partition approach for robust gait recognition based on gait template fusion

Wang, K., Liu, L., Ding, X., Yu, K., & Hu, G. (2021) · Frontiers of Information Technology & Electronic Engineering · doi:10.1631/fitee.2000377 · Cited by 4

A Deep Learning Approach for Biometric Security in Video Surveillance System Using Gait

Rajasab, N., & Rafi, M. (2022) · International Journal of Safety and Security Engineering · doi:10.18280/ijsse.120410 · Cited by 4

Deep Gait Relative Attribute using a Signed Quadratic Contrastive Loss

Hayashi, Y., Shehata, A., Makihara, Y., Muramatsu, D., & Yagi, Y. (2021) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr48806.2021.9411952 · Cited by 4

AN ENHANCED GAIT RECOGNITION SYSTEM BASED ON THE FEATURES FUSION METHODOLOGY WITH RECURRENT NEURAL NETWORK (RNN)

Upadhyay, J., & Gonsalves, T. (2022) · Indian Journal of Computer Science and Engineering · doi:10.21817/indjcse/2022/v13i5/221305042 · Cited by 3

Gait Recognition for 2-Second Walks Using Viewpoint Normalization and SlidingWindow Process

Limcharoen, P., Khamsemanan, N., & Nattee, C. (2023) · IEEE Access · doi:10.1109/access.2023.3266252 · Cited by 3

Gait Recognition by Jointing Transformer and CNN

Cai, M., Wang, M., & Zhang, S. (2023) · Lecture notes in computer science · doi:10.1007/978-981-99-8565-4_30 · Cited by 3

Smart gravimetric system based on Deep Learning for enhanced safety of accesses to public places

Addabbo, T., Fort, A., Mugnaini, M., Vignoli, V., Intravaia, M., Tani, M., Bianchini, M., Scarselli, F., & Corradini, B. T. (2021) · IEEE International Instrumentation and Measurement Technology Conference · doi:10.1109/i2mtc50364.2021.9460052 · Cited by 3

Fog cloud-assisted IoT-based human identification in construction sites from gait sequences

Ahmed, K., & Saini, M. (2022) · Multimedia Tools and Applications · doi:10.1007/s11042-022-13785-0 · Cited by 3

Gait Estimation of Occluded ROIs Using Interpolation Techniques and Testing Their Performance in Speed Variation in Gait

Bharti, J., Tomar, D. S., & Bhattacharjee, S. (2025) · Procedia Computer Science · doi:10.1016/j.procs.2025.04.637 · Cited by 2

OUMVLP-OF: Multi-View Large Population Gait Database With Dense Optical Flow and Its Performance Evaluation

Shehata, A., Castro, F. M., Guil, N., Marín-Jiménez, M. J., & Yagi, Y. (2025) · IEEE Access · doi:10.1109/access.2025.3570280 · Cited by 2

Model-Based Gait Recognition Using Multi-Level Graph Neural Networks With Stochastic Process and Skip Connections

Nattee, C., Khamsemanan, N., & Limcharoen, P. (2025) · IEEE Access · doi:10.1109/access.2025.3611837 · Cited by 2

A comprehensive survey on deep-learning based gait recognition for humans in the COVID-19 pandemic

Sayeed, M. S., Yusof, I., Abdullah, M. F. A., Bari, M. A., & Min, P. P. (2023) · Indonesian Journal of Electrical Engineering and Computer Science · doi:10.11591/ijeecs.v30.i2.pp882-902 · Cited by 2

Robust Gait Recognition Based on Spatio-Temporal Fusion Network

Wang, H., & Xu, X. (2023) · Neural Processing Letters · doi:10.1007/s11063-023-11370-6 · Cited by 2

Performance-aware Lightweight Dynamic Early-Exit-based Gait Authentication

Zouridakis, P., & Dinakarrao, S. M. P. (2022) · IEEE International Symposium on Circuits and Systems proceedings · doi:10.1109/iscas48785.2022.9937234 · Cited by 2

Gait Recognition with Various Data Modalities: A Review

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GAIT Technology for Human Recognition using CNN

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