Human Gait Recognition Based on Frame-by-Frame Gait Energy Images and Convolutional Long Short-Term Memory

Long Short-Term Memory

Hochreiter, S., & Schmidhuber, J. (1997) · Neural Computation · doi:10.1162/neco.1997.9.8.1735 · Cited by 102,318

Deep learning

LeCun, Y., Bengio, Y., & Hinton, G. (2015) · Nature · doi:10.1038/nature14539 · Cited by 84,126

Individual recognition using gait energy image

Han, J., & Bhanu, B. (2006) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2006.38 · Cited by 1,873

General Tensor Discriminant Analysis and Gabor Features for Gait Recognition

Tao, D., Li, X., Wu, X., & Maybank, S. J. (2007) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2007.1096 · Cited by 1,140

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

Sarkar, S., Phillips, P. J., Liu, Z., Vega, I. R., Grother, P., & Bowyer, K. W. (2005) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2005.39 · Cited by 1,133

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

Wu, Z., Huang, Y., Wang, L., Wang, X., & Tan, T. (2016) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2016.2545669 · Cited by 741

Automatic pixel-level multiple damage detection of concrete structure using fully convolutional network

Li, S., Zhao, X., & Zhou, G. (2019) · Computer-Aided Civil and Infrastructure Engineering · doi:10.1111/mice.12433 · Cited by 500

GEINet: View-invariant gait recognition using a convolutional neural network

Shiraga, K., Makihara, Y., Muramatsu, D., Echigo, T., & Yagi, Y. (2016) · 2016 International Conference on Biometrics (ICB) · doi:10.1109/icb.2016.7550060 · Cited by 468

Encoder–decoder network for pixel-level road crack detection in black-box images

Bang, S., Park, S., Kim, H., & Kim, H. (2019) · Computer-Aided Civil and Infrastructure Engineering · doi:10.1111/mice.12440 · Cited by 429

Image-based post-disaster inspection of reinforced concrete bridge systems using deep learning with Bayesian optimization

Liang, X. P. (2018) · Computer-Aided Civil and Infrastructure Engineering · doi:10.1111/mice.12425 · Cited by 406

Self-Supervised Learning for Electroencephalography

Rafiei, M. H., Gauthier, L. V., Adeli, H., & Takabi, D. (2022) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2022.3190448 · Cited by 333

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

State of the art in structural health monitoring of offshore and marine structures

Pezeshki, H., Adeli, H., Pavlou, D. G., & Siriwardane, S. C. (2023) · Proceedings of the Institution of Civil Engineers - Maritime Engineering · doi:10.1680/jmaen.2022.027 · Cited by 131

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

Continuous and simultaneous estimation of lower limb multi-joint angles from sEMG signals based on stacked convolutional and LSTM models

Lu, Y., Wang, H., Zhou, B., Wei, C., & Xu, S. (2022) · Expert Systems with Applications · doi:10.1016/j.eswa.2022.117340 · Cited by 104

Multi-View Gait Image Generation for Cross-View Gait Recognition

Chen, X., Luo, X., Weng, J., Luo, W., Li, H., & Tian, Q. C. (2021) · IEEE Transactions on Image Processing · doi:10.1109/tip.2021.3055936 · Cited by 102

Prosperous Human Gait Recognition: an end-to-end system based on pre-trained CNN features selection

Mehmood, A., Khan, M. A., Sharif, M. I., Khan, S. A., Shaheen, M., Saba, T., Riaz, N., & Ashraf, I. (2020) · Multimedia Tools and Applications · doi:10.1007/s11042-020-08928-0 · Cited by 86

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

TransGait: Multimodal-based gait recognition with set transformer

Li, G., Guo, L., Zhang, R., Qian, J., & Gao, S. (2022) · Applied Intelligence · doi:10.1007/s10489-022-03543-y · Cited by 71

Arbitrary Scale Super-Resolution for Medical Images

Zhu, J., Tan, C. Q., Yang, J., Yang, G., & Lió, P. (2021) · International Journal of Neural Systems · doi:10.1142/s0129065721500374 · Cited by 61

A Faster R-CNN and recurrent neural network based approach of gait recognition with and without carried objects

Ghosh, R. (2022) · Expert Systems with Applications · doi:10.1016/j.eswa.2022.117730 · Cited by 50

Deep Learning Approaches for Human Gait Recognition: A Review

Narayan, V., Awasthi, S., Fatima, N., Faiz, M., & Srivastava, S. (2023) · International Conference on Artificial Intelligence and Smart Communication (AISC) · doi:10.1109/aisc56616.2023.10085665 · Cited by 51

A Class-Imbalance Aware and Explainable Spatio-Temporal Graph Attention Network for Neonatal Seizure Detection

Raeisi, K., Khazaei, M., Tamburro, G., Croce, P., Comani, S., & Zappasodi, F. (2023) · International Journal of Neural Systems · doi:10.1142/s0129065723500466 · Cited by 52

Human Gait Recognition Based on Self-Adaptive Hidden Markov Model

Wang, X., Feng, S., & Yan, W. Q. (2019) · IEEE Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2019.2951146 · Cited by 47

Human Gait Recognition Using Deep Learning and Improved Ant Colony Optimization

Khan, A. A., Khan, M. A., Javed, M. Y., Alhaisoni, M. M., Tariq, U., Kadry, S., Choi, J.-I., & Nam, Y. (2021) · Computers, materials & continua/Computers, materials & continua (Print) · doi:10.32604/cmc.2022.018270 · Cited by 46

Evaluation of classification performance in human lower limb jump phases of signal correlation information and LSTM models

Lu, Y., Wang, H., Qi, Y., & Xi, H. (2020) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2020.102279 · Cited by 45

A Multi-Modal Gait Analysis-Based Detection System of the Risk of Depression

Shao, W., You, Z., Liang, L., Hu, X., Li, C., Wang, W. W., & Hu, B. (2021) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2021.3122299 · Cited by 47

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

Multiscaled Neural Autoregressive Distributed Lag: A New Empirical Mode Decomposition Model for Nonlinear Time Series Forecasting

Saâdaoui, F., & Messaoud, O. B. (2020) · International Journal of Neural Systems · doi:10.1142/s0129065720500392 · Cited by 40

Recent advances in biometrics-based user authentication for wearable devices: A contemporary survey

Liu, S., Shao, W., Li, T. K., Xu, W., & Song, L. (2021) · Digital Signal Processing · doi:10.1016/j.dsp.2021.103120 · Cited by 46

Uncertainty-Guided Voxel-Level Supervised Contrastive Learning for Semi-Supervised Medical Image Segmentation

Hua, Y., Shu, X., Wang, Z., & Zhang, L. (2022) · International Journal of Neural Systems · doi:10.1142/s0129065722500162 · Cited by 39

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Khan, M. A., Mittal, M., Goyal, L. M., & Roy, S. S. (2021) · Multimedia Tools and Applications · doi:10.1007/s11042-021-10811-5 · Cited by 41

Detection of Trees on Street-View Images Using a Convolutional Neural Network

Jodas, D. S., Yojo, T., Brazolin, S., Velasco, G. D. N., & Papa, J. P. (2021) · International Journal of Neural Systems · doi:10.1142/s0129065721500428 · Cited by 38

Gait classification through CNN-based ensemble learning

Wang, X., & Yan, K. (2020) · Multimedia Tools and Applications · doi:10.1007/s11042-020-09777-7 · Cited by 36

Deep learning pipelines for recognition of gait biometrics with covariates: a comprehensive review

Parashar, A., Parashar, A., Ding, W., Shekhawat, R. S., & Rida, I. (2023) · Artificial Intelligence Review · doi:10.1007/s10462-022-10365-4 · Cited by 36

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

Deep Learning and Kurtosis-Controlled, Entropy-Based Framework for Human Gait Recognition Using Video Sequences

Sharif, M. I., Khan, M. A., Alqahtani, A., Nazir, M., Alsubai, S., Binbusayyis, A., & Damaševičius, R. (2022) · Electronics · doi:10.3390/electronics11030334 · Cited by 35

Human Action Recognition Using Deep Learning Methods

Yu, Z., & Yan, W. Q. (2020) · International Conference on Image and Vision Computing New Zealand (IVCNZ) · doi:10.1109/ivcnz51579.2020.9290594 · Cited by 28

Convolutional Bi-LSTM Based Human Gait Recognition Using Video Sequences

Amin, J., Anjum, M. A., Sharif, M., Kadry, S., Nam, Y., & Wang‎, S. (2021) · Computers, materials & continua/Computers, materials & continua (Print) · doi:10.32604/cmc.2021.016871 · Cited by 31

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Liu, X., Neuyen, M., & Yan, W. Q. (2020) · Communications in computer and information science · doi:10.1007/978-981-15-3651-9_7 · Cited by 26

Exploring Deep Learning Methods for Computer Vision Applications across Multiple Sectors: Challenges and Future Trends

Ganesh, N., Shankar, R., Mahdal, M., Murugan, J. S., Chohan, J. S., & Kalita, K. (2023) · Computer Modeling in Engineering & Sciences · doi:10.32604/cmes.2023.028018 · Cited by 34

Gait Recognition Using Optical Motion Capture: A Decision Fusion Based Method

Wang, L., Li, Y., Xiong, F., & Zhang, W. (2021) · Sensors · doi:10.3390/s21103496 · 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

Non-local gait feature extraction and human identification

Wang, X., & Yan, W. Q. (2020) · Multimedia Tools and Applications · doi:10.1007/s11042-020-09935-x · Cited by 22

A comprehensive review of AI-Based detection of Arrhythmia using Electrocardiogram (ECG)

Ayyub, A., Politis, C., & Usman, M. A. (2025) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2025.110594 · Cited by 18

Behavior detection and evaluation based on multi-frame MobileNet

Liu, L., Wang, X., Bao, Q., & Li, X. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-023-16150-x · Cited by 17

Deep Learning Methods for Human Behavior Recognition

Jia, L., Nguyen, M., & Yan, W. Q. (2020) · International Conference on Image and Vision Computing New Zealand (IVCNZ) · doi:10.1109/ivcnz51579.2020.9290640 · Cited by 17

Human Gait Recognition Based on Sequential Deep Learning and Best Features Selection

Hanif, C. A., Mughal, M. A., Khan, M. A., Tariq, U., Kim, Y. J., & Cha, J. (2023) · Computers, materials & continua/Computers, materials & continua (Print) · doi:10.32604/cmc.2023.038120 · Cited by 16

Advances in Vision-Based Gait Recognition: From Handcrafted to Deep Learning

Mogan, J. N., Lee, C. P., & Lim, K. M. (2022) · Sensors · doi:10.3390/s22155682 · Cited by 15

A comprehensive review of gait analysis using deep learning approaches in criminal investigation

Aung, S. T. Y., & Kusakunniran, W. (2024) · PeerJ Computer Science · doi:10.7717/peerj-cs.2456 · Cited by 14

Human Silhouette and Skeleton Video Synthesis Through Wi-Fi Signals

Avola, D., Cascio, M., Cinque, L., Fagioli, A., & Foresti, G. L. (2022) · International Journal of Neural Systems · doi:10.1142/s0129065722500150 · Cited by 14

Enhanced Multitask Learning for Hash Code Generation of Palmprint Biometrics

Chen, L., Leng, L., Yang, Z., & Teoh, A. B. J. (2024) · International Journal of Neural Systems · doi:10.1142/s0129065724500205 · Cited by 13

Cross-view gait recognition based on residual long short-term memory

Wen, J., & Wang, X. (2021) · Multimedia Tools and Applications · doi:10.1007/s11042-021-11107-4 · Cited by 12

Deep Learning-driven Front-Following within Close Proximity: a Hands-Free Control Model on a Smart Walker

Zhao, C., Guo, W., Rongwei, W., Wang, Z., & Wu, C. (2022) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra46639.2022.9811910 · Cited by 12

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Sikandar, T., Rabbi, M. F., Ghazali, K. H., Altwijri, O., Alqahtani, M., Almijalli, M., Altayyar, S. S., & Ahamed, N. U. (2021) · Sensors · doi:10.3390/s21082836 · Cited by 12

Visual gait recognition based on convolutional block attention network

Wang, X., & Hu, S. (2022) · Multimedia Tools and Applications · doi:10.1007/s11042-022-12831-1 · Cited by 11

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

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Mehtab, S., Yan, W. Q., & Narayanan, A. (2021) · International Conference on Image and Vision Computing New Zealand (IVCNZ) · doi:10.1109/ivcnz54163.2021.9653358 · Cited by 11

Deep multi-convolutional stacked capsule network fostered human gait recognition from enhanced gait energy image

Nithyakani, P., & Ukrit, M. F. (2023) · Signal Image and Video Processing · doi:10.1007/s11760-023-02851-1 · Cited by 10

Human Action Recognition From Digital Videos Based on Deep Learning

Liang, C., Jia, L., & Yan, W. Q. (2022) · International Conference on Control and Computer Vision (ICCCV) · doi:10.1145/3561613.3561637 · Cited by 10

Computer Vision-Based Gait Recognition on the Edge: A Survey on Feature Representations, Models, and Architectures

Salcedo, E. (2024) · Journal of Imaging · doi:10.3390/jimaging10120326 · Cited by 10

Gait recognition methods in the task of biometric human identification

Purish, S. V., & Lobachev, M. V. (2023) · Herald of Advanced Information Technology · doi:10.15276/hait.06.2023.1 · Cited by 11

A bidirectional Siamese recurrent neural network for accurate gait recognition using body landmarks

Progga, P. H., Rahman, M. J., Biswas, S., Ahmed, S., Anwary, A. R., & Shatabda, S. (2024) · Neurocomputing · doi:10.1016/j.neucom.2024.128313 · Cited by 9

A method for balancing a multi-labeled biomedical dataset

Mukhin, A., Kilbas, I., Александрович, П. Р., Ilyasova, N. Y., & Kupriyanov, A. V. (2022) · Integrated Computer-Aided Engineering · doi:10.3233/ica-220676 · Cited by 8

Gait recognition based on sparse linear subspace

Wen, J., & Wang, X. (2021) · IET Image Processing · doi:10.1049/ipr2.12260 · Cited by 7

Human identification based on Gait Manifold

Wang, X., & Yan, W. Q. (2022) · Applied Intelligence · doi:10.1007/s10489-022-03818-4 · Cited by 7

Research Progress on Tunable Absorbers for Various Wavelengths Based on Metasurfaces

Jiang, K., Feng, H., Gu, M., Jing, X., & Li, C. (2025) · Photonics · doi:10.3390/photonics12100968 · 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

Gait-Enhance:Robust Gait Recognition of Complex Walking Patterns Based on WiFi CSI

Yang, J., Liu, Y., Wu, Y. F., Yang, P., & Liu, Z. (2023) · IEEE Smart World Congress (SWC) · doi:10.1109/swc57546.2023.10449176 · Cited by 5

Abnormal Behavior Recognition Based on 3D Dense Connections

Chen, W. R., Yu, Z., Yang, C., & Lu, Y. (2024) · International Journal of Neural Systems · doi:10.1142/s0129065724500497 · Cited by 5

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Pundir, A., & Sharma, M. (2023) · International Conference for Innovation in Technology (INOCON) · doi:10.1109/inocon57975.2023.10101267 · Cited by 5

Gait identification based on deepwalk features using CNN and LSTM: an advanced biometric approach

Tiwari, R. S., Das, T. K., Tripathy, A. K., & Li, K. (2025) · Telecommunication Systems · doi:10.1007/s11235-025-01319-6 · Cited by 4

Convolutional Neural Networks and Recurrent Neural Networks

Yan, W. Q. (2023) · Texts in computer science · doi:10.1007/978-981-99-4823-9_3 · Cited by 8

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Ramakić, A., Bundalo, Z., & Bundalo, D. (2024) · Journal of Circuits Systems and Computers · doi:10.1142/s0218126624502086 · Cited by 4

DeepNet-Gait: Human Identification by Gait Using Convolutional Neural Network Model

Rani, V., & Kumar, M. (2023) · International Conference on Signal Processing and Integrated Networks (SPIN) · doi:10.1109/spin57001.2023.10117067 · Cited by 3

Gait recognition via weighted global-local feature fusion and attention-based multiscale temporal aggregation

Xu, Y., Xi, H., Ren, K., Zhu, Q., & Hu, C. (2025) · Journal of Electronic Imaging · doi:10.1117/1.jei.34.1.013002 · Cited by 3

Integration of Face and Gait Recognition via Transfer Learning: A Multiscale Biometric Identification Approach

Ahmed, D. M., & Mahmood, B. S. (2023) · Traitement du signal · doi:10.18280/ts.400535 · Cited by 3

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Musalhi, N. A., & Çelebi, E. (2024) · Traitement du signal · doi:10.18280/ts.410228 · Cited by 3

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Yousef, R. N., Ata, M. M., Rashed, A. E. E., Badawy, M., Elhosseini, M. A., & Bahgat, W. M. (2024) · Biomimetics · doi:10.3390/biomimetics9060364 · Cited by 2

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Hamid, J. A., N, R. P. K., Kaur, A., Chohan, M. K., Dasi, S., Kumar, P., Singh, D., & Alkhayyat, A. H. (2025) · National Academy Science Letters · doi:10.1007/s40009-025-01631-4 · Cited by 2

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Lv, M., Feng, H., Jin, Y., & Tian, Y. (2025) · Photonics · doi:10.3390/photonics12100947 · Cited by 4

Generation and Manipulation of Perfect Vortex Beams via Metasurfaces

Feng, K., Feng, H., Gu, M., Li, C., & Jing, X. M. (2025) · Annalen der Physik · doi:10.1002/andp.202500426 · Cited by 2

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Song, X., Qian, K., & Tang, S. (2026) · Bioengineering · doi:10.3390/bioengineering13030272 · Cited by 2

Systematic Literature Review: Human Gait Cycle Model Using Image-Temporal Feature

Jamal, I. H., Izhar, C. A. A., Fauzilan, A. S., Maruzuki, M. I. F., Hussain, Z., & Rahman, M. F. A. (2021) · IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE) · doi:10.1109/icraie52900.2021.9703989 · Cited by 2

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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

GaitDONet: Gait Recognition Using Deep Features Optimization and Neural Network

Khan, M. A., Khan, A. A., Alhaisoni, M. M., Alqahtani, A., Armghan, A., Althubiti, S. A., Alenezi, F. S., Mey, S., & Nam, Y. (2023) · Computers, materials & continua/Computers, materials & continua (Print) · doi:10.32604/cmc.2023.033856 · Cited by 2

Pedestrian Re-Identification Based on Gait Analysis

Shan, Y., Yu, G., & Gao, Y. (2023) · IEEE Access · doi:10.1109/access.2023.3320577 · Cited by 2

Biometric Authentication using Gait Recognition

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Assessing the Robustness of Deep Learning-Based Gait Recognition Systems Against Adversarial Attacks

Saoudi, E. M., Andaloussi, S. J., & Jaafari, J. (2024) · International Conference on Networking, Information Systems & Security (NISS) · doi:10.1145/3659677.3659824 · Cited by 2

KiRV: Robust Human Identification via Multimodal Learning Based on Kinetic Gait Features of Radar and Vision

Deng, L., Pei, J., Song, Y., Huo, W., Zhang, Y., & Huang, Y. (2025) · IEEE Internet of Things Journal · doi:10.1109/jiot.2025.3550532 · Cited by 2

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Chen, M., Li, Z., & He, Y. (2025) · International Conference on Image Processing, Machine Learning and Pattern Recognition (IPMLPR) · doi:10.1145/3759928.3759938 · Cited by 2

Introduction

Yan, W. Q. (2020) · Texts in computer science · doi:10.1007/978-3-030-61081-4_1 · Cited by 2

Comparison Between Face and Gait Human Recognition Using Enhanced Convolutional Neural Network

Sadeq, F. E., & Al-Ta’i, Z. T. M. (2023) · Journal of Applied Engineering and Technological Science (JAETS) · doi:10.37385/jaets.v5i1.2806 · Cited by 2

An Enhanced Human Gait Recognition System using UALNN Classifier

Thomas, K. T., & Pushpalatha, K. P. (2024) · IETE Journal of Research · doi:10.1080/03772063.2024.2351563 · Cited by 1

Controllable multi-focal terahertz metalens based on vanadium dioxide

Wu, Y. M., Tao, Y. M., Feng, H., Tian, Y., Gu, M., Han, J., & Yu, M. (2025) · Journal of Modern Optics · doi:10.1080/09500340.2025.2564288 · Cited by 1

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Review on all-dielectric metasurface encryption technology

Wang, Y., Gu, M., Tian, Y., Li, C., Jin, Y., Wang, L., & Jing, X. (2025) · Defence Technology · doi:10.1016/j.dt.2025.11.036 · Cited by 1

GGCN: Gait Recognition with Generate Network and Convolutional Neural Network

Qin, H., Chen, Z., Guo, Q., Wu, Q., & Lu, M. (2026) · Journal of Visual Communication and Image Representation · doi:10.1016/j.jvcir.2026.104790 · Cited by 1

Deep supervised hashing for gait retrieval

Sayeed, M. S., Min, P. P., & Ong, T. S. (2021) · F1000Research · doi:10.12688/f1000research.51368.1 · Cited by 1

Deep supervised hashing for gait retrieval

Sayeed, M. S., Min, P. P., & Ong, T. S. (2022) · F1000Research · doi:10.12688/f1000research.51368.2 · Cited by 1

HPO Using Dwarf Mongoose Optimization in the GAN Model for Human Gait Recognition

Karthik, M. G., Mantena, S. V., Chintamaneni, P., Chennupalli, S., Naladesi, S. Y., & Vatambeti, R. (2023) · International Journal of Safety and Security Engineering · doi:10.18280/ijsse.130206 · Cited by 1

Human Action Recognition Based on YOLOv7

Liang, C., & Yan, W. Q. (2024) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3693-1738-9.ch006 · Cited by 1

Developing of a multi-angle and varied walking conditions dataset for human gait recognition

Zazueta, J. M. B., Rodriguez-Rangel, H., Puig, V., Medrano-Diaz, M. A., Gregorio, S. I. F., & Morales-Rosales, L. A. (2024) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2024.109404 · Cited by 1

Gait Recognition Analysis for Human Identification Analysis- A Hybrid Deep Learning ProcessPreprint

Mathivanan, B., & Perumal, P. (2021) · Research Square · doi:10.21203/rs.3.rs-549846/v1 · Cited by 1

Empirical Analysis for Earlier Diagnosis of Alzheimer’s Disease Using Deep Learning

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Introduction

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