Background subtraction in real applications: Challenges, current models and future directions

Robust principal component analysis?

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Wallflower: principles and practice of background maintenance

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Efficient adaptive density estimation per image pixel for the task of background subtraction

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Subject-Specific Human Modeling for Human Pose Estimation

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Reviewing ViBe, a Popular Background Subtraction Algorithm for Real-Time Applications

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Background subtraction via regional multi-feature-frequency model in complex scenes

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Joint fuzzy background and adaptive foreground model for moving target detection

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Filtering Empty Video Frames for Efficient Real-Time Object Detection

Liu, Y., & Kang, K. (2024) · Sensors · doi:10.3390/s24103025 · Cited by 9

An adaptive background modeling for foreground detection using spatio-temporal features

Mohanty, S. K., & Rup, S. (2020) · Multimedia Tools and Applications · doi:10.1007/s11042-020-09552-8 · Cited by 9

Light-Weight Mixed Stage Partial Network for Surveillance Object Detection with Background Data Augmentation

Chen, P.-Y., Hsieh, J.-W., Gochoo, M., & Chen, Y. (2021) · Proceedings - International Conference on Image Processing · doi:10.1109/icip42928.2021.9506212 · Cited by 9

Multispectral background subtraction with deep learning

Liu, R., Ruichek, Y., & Bagdouri, M. E. (2021) · Journal of Visual Communication and Image Representation · doi:10.1016/j.jvcir.2021.103267 · Cited by 9

Unsupervised Anomaly Detection from Time-of-Flight Depth Images

Schneider, P., Rambach, J. R., Mirbach, B., & Stricker, D. (2022) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw56347.2022.00037 · Cited by 11

Boxing Punch Detection with Single Static Camera

Stefański, P., Jach, T., & Kozak, J. (2024) · Entropy · doi:10.3390/e26080617 · Cited by 8

To Turn or Not To Turn, SafeCross is the Answer

Wu, B., He, Y., Dong, Z., Wan, J., Zhang, J., & Shi, W. (2022) · IEEE International Conference on Distributed Computing Systems (ICDCS) · doi:10.1109/icdcs54860.2022.00047 · Cited by 8

Real-time Engagement Detection from Facial Features

Marqués-Villarroya, S., Gamboa‐Montero, J. J., Bernardino, A. J. M., Gómez, M. M., Castillo, J. C., & Salichs, M. A. (2022) · IEEE International Conference on Development and Learning (ICDL) · doi:10.1109/icdl53763.2022.9962228 · Cited by 9

An Improved Kuhn Munkres Algorithm for Ship Matching in Optical Satellite Images

Liu, S., Qu, C., Xu, M., Wan, J., Sheng, H., Zeng, Z., & Cui, J. (2023) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2023.3277117 · Cited by 8

Extracting Visual Micro-Doppler Signatures From Human Lips Motion Using UoG Radar Sensing Data for Hearing Aid Applications

Saeed, U., Shah, S. A., Ghadi, Y. Y., Khan, M. Z., Ahmad, J. E., Shah, S. I., Hameed, H., & Abbasi, Q. H. (2023) · IEEE Sensors Journal · doi:10.1109/jsen.2023.3308972 · Cited by 8

X-Stream: A Flexible, Adaptive Video Transformer for Privacy-Preserving Video Stream Analytics

Feng, D., Wang, L., Chen, S. Y., Tung, L., & Liu, F. (2024) · IEEE Conference on Computer Communications (INFOCOM) · doi:10.1109/infocom52122.2024.10621341 · Cited by 8

Instance-Level Moving Object Segmentation from a Single Image with Events

Wan, Z., Fan, B., Hui, L., Dai, Y., & Lee, G. H. (2025) · International Journal of Computer Vision · doi:10.1007/s11263-025-02380-z · Cited by 8

ISAIR: Deep inpainted semantic aware image representation for background subtraction

Esfahani, M. A., Jamadi, A., & Esfahani, M. A. (2022) · Expert Systems with Applications · doi:10.1016/j.eswa.2022.117947 · Cited by 8

A Fog-Assisted Framework for Intelligent Video Preprocessing in Cloud-Based Video Surveillance as a Service

Ravindran, S., & Aghila, G. (2022) · IEEE Transactions on Sustainable Computing · doi:10.1109/tsusc.2022.3177688 · Cited by 7

Real-Time Hysteresis Foreground Detection in Video Captured by Moving Cameras

Ghahremannezhad, H., Shi, H., & Liu, C. (2022) · IEEE International Conference on Imaging Systems and Techniques (IST) · doi:10.1109/ist55454.2022.9827719 · Cited by 7

A computationally efficient moving object detection technique using tensor QR decomposition based TRPCA framework

Sabat, N., Subodh Raj, M. S., George, S. N., & Kumar, T. K. S. (2023) · Journal of Visual Communication and Image Representation · doi:10.1016/j.jvcir.2023.103785 · Cited by 7

Real-time Background Subtraction under Varying Lighting Conditions

Liang, S., & Baker, D. (2023) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra48891.2023.10160223 · Cited by 7

Vision Fourier transformer empowered multi-modal imaging system for ethane leakage detection

Bin, J., Rogers, S., & Liu, Z. (2024) · Information Fusion · doi:10.1016/j.inffus.2024.102266 · Cited by 7

LD‐Net : A novel one‐stage knowledge distillation algorithm for lightning detection network

Fu, J., Li, Y., Liu, J., Ji, Y., & Zhong, J. (2024) · Meteorological Applications · doi:10.1002/met.2171 · Cited by 7

ManiDec: Manifold Constrained Low-Rank and Sparse Decomposition

Liu, J., He, D., Zeng, X., Wang, M., Xiu, X., Liu, W., & Li, W. (2019) · IEEE Access · doi:10.1109/access.2019.2935235 · Cited by 7

Pre-processing framework with virtual mono-layer sequence of boxes for video based vehicle detection applications

Sankaranarayanan, M., Mala, C., & Mathew, S. (2020) · Multimedia Tools and Applications · doi:10.1007/s11042-020-09587-x · Cited by 7

Maritime filtering for images and videos

Chan, Y.-T. (2021) · Signal Processing Image Communication · doi:10.1016/j.image.2021.116477 · Cited by 7

Cascaded Feature-Mask Fusion for Foreground Segmentation

Xu, C., Liu, H., Li, T., Zhang, Y., Tian, L., & Li, G. (2022) · IEEE Open Journal of Intelligent Transportation Systems · doi:10.1109/ojits.2022.3170075 · Cited by 7

Performance analysis of U-Net with hybrid loss for foreground detection

Kalsotra, R., & Arora, S. (2022) · Multimedia Systems · doi:10.1007/s00530-022-01014-5 · Cited by 7

Adaptive Vector-Based Sample Consensus Model for Moving Target Detection in Infrared Video

Zhang, Y., Leng, K., & Park, K. (2022) · IEEE Geoscience and Remote Sensing Letters · doi:10.1109/lgrs.2022.3150760 · Cited by 7

Dynamic Background Subtraction by Generative Neural Networks

Bahri, F., & Ray, N. (2022) · IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) · doi:10.1109/avss56176.2022.9959543 · Cited by 7

SMod: Scene-Specific-Prior–Based Moving Object Detection for Airport Apron Surveillance Systems

Zhang, X., Qiao, Y., Yang, Y., & Wang, S. (2021) · IEEE Intelligent Transportation Systems Magazine · doi:10.1109/mits.2021.3122926 · Cited by 6

Implementation of Motion Detection Methods on Embedded Systems: A Performance Comparison

Sehairi, K., & Chouireb, F. (2023) · International Journal of Technology · doi:10.14716/ijtech.v14i3.5950 · Cited by 6

Effective Fusion Method on Silhouette and Pose for Gait Recognition

Zhao, Y., Liu, R., Xue, W., Yang, M., Shiraishi, M., Awai, S., Maruyama, Y., Yoshioka, T., & Konno, T. (2023) · IEEE Access · doi:10.1109/access.2023.3317437 · Cited by 6

A quantum moving target segmentation algorithm for grayscale video based on background difference method

Wang, L., Liu, Y., Meng, F., Liu, W., Zhang, Z., & Yu, X. (2024) · EPJ Quantum Technology · doi:10.1140/epjqt/s40507-024-00234-0 · Cited by 6

A Multi-Scale Contrast Preserving Encoder-Decoder Architecture for Local Change Detection From Thermal Video Scenes

Panda, M. K., Subudhi, B. N., Veerakumar, T., Jakhetiya, V., & Bouwmans, T. (2024) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2024.3447237 · Cited by 6

Automatic foreground extraction from imperfect backgrounds using multi-agent consensus equilibrium

Wang, X., Juang, J., & Chan, S. H. (2020) · Journal of Visual Communication and Image Representation · doi:10.1016/j.jvcir.2020.102907 · Cited by 6

Comparison of Background Subtraction and Frame Differencing Methods for Indoor Moving Object Detection

Jusman, Y., Hinggis, L., Wiyagi, R. O., Isa, N. A. M., & Mujaahid, F. (2020) · International Conference on Information Technology, Advanced Mechanical and Electrical Engineering (ICITAMEE) · doi:10.1109/icitamee50454.2020.9398484 · Cited by 6

Tensor based completion meets adversarial learning: A win–win solution for change detection on unseen videos

Kajo, I., Kas, M., Ruichek, Y., & Kamel, N. (2022) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2022.103584 · Cited by 6

The trade‐off between accuracy and the complexity of real‐time background subtraction

Hossain, M. A., Nguyen, V., & Huh, E. (2020) · IET Image Processing · doi:10.1049/ipr2.12026 · Cited by 6

Automatic monitoring of activity intensity in a chicken flock using a computer vision-based background image subtraction technique: An experimental infection study with fowl adenovirus

Iseki, H., Furukawa, E., Shimasaki, T., & Higaki, S. (2025) · Smart Agricultural Technology · doi:10.1016/j.atech.2025.100821 · Cited by 5

Deep learning for Amur tiger re-identification in camera traps: A tool assisting population monitoring and spatio-temporal analysis

Ma, Y., Tan, M., Liu, X., Zhang, Y., Xu, Z., Sun, W., Ge, J., & Feng, L. (2025) · Ecological Indicators · doi:10.1016/j.ecolind.2025.113227 · Cited by 9

NeuroHSMD: Neuromorphic Hybrid Spiking Motion Detector

Machado, P., Ferreira, J. F., Oikonomou, A., & McGinnity, T. M. (2023) · ACM Transactions on Reconfigurable Technology and Systems · doi:10.1145/3588318 · Cited by 5

Embedded and real time vehicle classification system with occlusion handling

Moutakki, Z., Ouloul, I. M., Amghar, A., Motahhir, S., & Afdel, K. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-023-14852-w · Cited by 5

TSOM: Small object motion detection neural network inspired by avian visual circuit

Hu, P., Zhang, X., Li, M., Zhu, Y., & Shi, L. (2024) · Neural Networks · doi:10.1016/j.neunet.2024.106881 · Cited by 5

Manifold constrained joint sparse learning via non-convex regularization

Liu, J., Xiu, X., Jiang, X., Liu, W., Zeng, X., Wang, M., & Chen, H. (2021) · Neurocomputing · doi:10.1016/j.neucom.2021.06.008 · Cited by 5

Efficient and Robust Background Modeling with Dynamic Mode Decomposition

Krake, T., Bruhn, A., Eberhardt, B., & Weiskopf, D. (2022) · Journal of Mathematical Imaging and Vision · doi:10.1007/s10851-022-01068-0 · Cited by 5

XDMOM: A Real-Time Moving Object Detection System Based on a Dual-Spectrum Camera

Shi, B., Gu, W., & Sun, X. (2022) · Sensors · doi:10.3390/s22103905 · Cited by 5

Intrusion Distance and Reaction Time Estimation for Safe and Efficient Industrial Robots

Rashid, A., Naser, I. A., Hou, S., Bdiwi, M., Pütz, M., & Ihlenfeldt, S. (2022) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra46639.2022.9811900 · Cited by 5

Moving Object Detection in Video Sequences Based on a Two-Frame Temporal Information CNN

Chacon-Murguia, M. I., & Pando, A. G. (2022) · Neural Processing Letters · doi:10.1007/s11063-022-11092-1 · Cited by 6

A Quantum Moving Target Segmentation Algorithm for Grayscale Video

Liu, W., Wang, L., & Wu, Q. (2023) · Advanced Quantum Technologies · doi:10.1002/qute.202300248 · Cited by 5

The Development of a Stereo Vision System to Study the Nutation Movement of Climbing Plants

Ruiz-Melero, D. R., Ponkshe, A., Calvo, P., & Garcı́a-Mateos, G. (2024) · Sensors · doi:10.3390/s24030747 · Cited by 5

Leveraging foreground–background cues for semantically-driven, training-free moving object detection

Şımşek, E., Negin, F., Özyer, G. T., & Özyer, B. (2024) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2024.108873 · Cited by 5

Optimizing motion detection performance: Harnessing the power of squeeze and excitation modules

Mpofu, J. B., Li, C., Xinyan, G., & Su, X. (2024) · PLoS ONE · doi:10.1371/journal.pone.0308933 · Cited by 5

A Panoramic Review on Cutting-Edge Methods for Video Anomaly Localization

Nayak, R., Mishra, S. K., Dalai, A. K., Pati, U. C., & Das, S. K. (2024) · IEEE Access · doi:10.1109/access.2024.3510039 · Cited by 5

OutfitAI: shop the outfit with a deep learning-based intelligent expert system

Balloni, E., Pietrini, R., Frontoni, E., Mancini, A., & Paolanti, M. (2025) · Multimedia Tools and Applications · doi:10.1007/s11042-025-20753-x · Cited by 7

Feature extraction of moving objects using background subtraction technique for robotic applications

Thotapalli, P. K., Chintamreddy, V. K., & Reddy, B. C. M. (2020) · International Journal of Intelligent Robotics and Applications · doi:10.1007/s41315-020-00145-0 · Cited by 5

Road Traffic Congestion (TraCo) Estimation Using Multi-Layer Continuous Virtual Loop (MCVL)

Sankaranarayanan, M., Mala, C., & Mathew, S. (2021) · International Journal of Intelligent Information Technologies · doi:10.4018/ijiit.2021040103 · Cited by 5

Improved Vehicle Detection Accuracy and Processing Time for Video Based ITS Applications

Sankaranarayanan, M., Mala, C., & Mathew, S. (2022) · SN Computer Science · doi:10.1007/s42979-022-01130-z · Cited by 5

Dynamic strategy to use optimum memory space in real-time video surveillance

Biswas, T., Bhattacharya, D., & Mandal, G. (2023) · Journal of Ambient Intelligence and Humanized Computing · doi:10.1007/s12652-023-04521-z · Cited by 6

Classification of Punches in Olympic Boxing Using Static RGB Cameras

Stefański, P., Jach, T., & Kozák, J. T. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-41456-5_41 · Cited by 5

BgSubNet: Robust Semisupervised Background Subtraction in Realistic Scenes

Chung, N. M., & Ha, S. V. (2024) · IEEE Sensors Journal · doi:10.1109/jsen.2024.3358181 · Cited by 5

Deep Autoencoders with Value-at-Risk Thresholding for Unsupervised Anomaly Detection

Akhriev, A., & Mareček, J. (2019) · IEEE International Symposium on Multimedia (ISM) · doi:10.1109/ism46123.2019.00045 · Cited by 5

Automatically localising ROIs in hyperspectral images using background subtraction techniques

Shah, M., Cave, V. M., & dos Reis, M. M. (2020) · International Conference on Image and Vision Computing New Zealand (IVCNZ) · doi:10.1109/ivcnz51579.2020.9290728 · Cited by 5

Key-Frame Detection and Video Retrieval Based on DC Coefficient-Based Cosine Orthogonality and Multivariate Statistical Tests

Kalakoti, G., & Prabakaran, G. (2020) · Traitement du signal · doi:10.18280/ts.370509 · Cited by 5

Study of Traditional, Artificial Intelligence and Machine Learning Based Approaches for Moving Object Detection

Joshi, A., Amrita, A., Mathur, R. S., Kumar, N., & Tripathi, P. (2024) · Wiley eBooks · doi:10.1002/9781394200733.ch9 · Cited by 6

GAI-Enabled Task-Driven Semantic Communication for Surveillance Video

Chen, M., Ma, W., Wang, L., Bazzi, W. M., Wang, K., & Mumtaz, S. (2025) · IEEE Transactions on Communications · doi:10.1109/tcomm.2025.3649653 · Cited by 4

SSRNet: A Deep Learning Network via Spatial‐Based Super‐resolution Reconstruction for Cell Counting and Segmentation

Deng, L., Zhou, Q., Wang‎, S., & Zhang, Y. (2023) · Advanced Intelligent Systems · doi:10.1002/aisy.202300185 · Cited by 4

Background subtraction for video sequence using deep neural network

Dai, Y., & Yang, L. (2024) · Multimedia Tools and Applications · doi:10.1007/s11042-024-18843-3 · Cited by 4

LLM-drone: aerial additive manufacturing with drones planned using large language models

Merrill, C., Raman, A., George, A., & Farimani, A. B. (2025) · Construction Robotics · doi:10.1007/s41693-025-00162-0 · Cited by 10

Nonsmooth rank-one matrix factorization landscape

Josz, C., & Lai, L. (2021) · Optimization Letters · doi:10.1007/s11590-021-01819-9 · Cited by 4

Image-based research methods for mapping tourist behaviour: smart photos

Zhan, X., Guo, F. B., & Roberts, E. (2023) · Tourism Recreation Research · doi:10.1080/02508281.2023.2196487 · Cited by 4

A Novel Background Modeling Based on Keyframe and Particle Shape Property for Surveillance Video

Fan, Y., He, X., Lin, Y., & Cai, Z. (2023) · IEEE Access · doi:10.1109/access.2023.3329816 · Cited by 4

Smart Traffic Management System using Background Subtraction

Kottha, B. R., Anuradha, T., Penumacha, N. K., & Gadde, H. V. (2024) · International Conference on Expert Clouds and Applications (ICOECA) · doi:10.1109/icoeca62351.2024.00095 · Cited by 4

Masked-RPCA: Moving Object Detection With an Overlaying Model

Khalilian-Gourtani, A., Minaee, S., & Wang, Y. (2020) · IEEE Open Journal of Signal Processing · doi:10.1109/ojsp.2020.3039325 · Cited by 4

Novel Moving-Target Detection Using A Hybrid of RGB Images and LiDAR Point-Clouds

Tian, R., Wu, H., Ye, J., & Wu, Y. (2020) · IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB) · doi:10.1109/bmsb49480.2020.9379476 · Cited by 4

Hyperspectral Image Analysis for Automatic Detection and Discrimination of Residual Manufacturing Contaminants

Vali, A., Kramer, P., Strzoda, R., Comai, S., Gigler, A. M., & Matteucci, M. (2021) · IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) · doi:10.1109/etfa45728.2021.9613640 · Cited by 4

High-Speed Large-Scale Imaging Using Frame Decomposition From Intrinsic Multiplexing of Motion

Li, D., Bian, L., & Zhang, J. (2022) · IEEE Journal of Selected Topics in Signal Processing · doi:10.1109/jstsp.2022.3164524 · Cited by 4

High-Speed Tracking with Mutual Assistance of Feature Filters and Detectors

Matsuo, A., & Yamakawa, Y. (2023) · Sensors · doi:10.3390/s23167082 · Cited by 4

Computer Vision-based Approaches, Datasets, and Applications of Smart Parking Systems: A Review

Hadi, R. A., George, L. E., & Ahmed, Z. J. (2024) · Iraqi Journal of Science · doi:10.24996/ijs.2024.65.2.32 · Cited by 4

Deep Autoencoder Architectures For Foreground Object Detection In Video Sequences Based On Probabilistic Mixture Models

García-González, J., Molina‐Cabello, M. A., Luque‐Baena, R. M., Ortiz-de-Lazcano-Lobato, J. M., & López‐Rubio, E. (2020) · Proceedings - International Conference on Image Processing · doi:10.1109/icip40778.2020.9190834 · Cited by 4

Multi-Channel Fused Lasso for Motion Detection in Dynamic Video Scenarios

Rong, G., Liu, X., Yang, J., & Yue, H. (2023) · IEEE Transactions on Consumer Electronics · doi:10.1109/tce.2023.3341908 · Cited by 3

Fog-Assisted Abnormal Motion Detection System: A Semantic Ontology Approach

Amshavalli, R. S., & Kalaivani, J. (2024) · Circuits Systems and Signal Processing · doi:10.1007/s00034-024-02725-y · Cited by 3

A robust image descriptor-local radial grouped invariant order pattern

Wang, X., Xu, Y., & Niu, P. (2024) · Information Sciences · doi:10.1016/j.ins.2024.121675 · Cited by 3

An improved ViBe-based approach for moving object detection

Tang, G., Ni, J., Shi, P., Li, Y., & Zhu, J. (2022) · Intelligence & Robotics · doi:10.20517/ir.2022.07 · Cited by 3

Illumination-Aware Image Segmentation for Real-Time Moving Cast Shadow Suppression

Ghahremannezhad, H., Shi, H., & Liu, C. (2022) · IEEE International Conference on Imaging Systems and Techniques (IST) · doi:10.1109/ist55454.2022.9827738 · Cited by 3

NeSe: Near-Sensor Event-Driven Scheme for Low Power Energy Harvesting Sensors

Tabrizchi, S., Morsali, M., Angizi, S., & Roohi, A. (2023) · IEEE International Symposium on Circuits and Systems proceedings · doi:10.1109/iscas46773.2023.10181329 · Cited by 3

KDE-Based Simultaneous Background Model Learning and Entropy-Based Fusion of Cascaded Features for Video Object Segmentation With Shadow Removal

Sahoo, S., & Nanda, P. K. (2023) · IEEE Access · doi:10.1109/access.2023.3299872 · Cited by 3

Application of dynamic image analysis to the optical characterisation of fibrous bulk material

Lunewski, J., & Schmidt, E. H. F. (2023) · Particuology · doi:10.1016/j.partic.2023.11.015 · Cited by 3

Human Event Recognition in Smart Classrooms Using Computer Vision: A Systematic Literature Review

Córdoba-Tlaxcalteco, M. L., & Benítez–Guerrero, E. (2023) · Programming and Computer Software · doi:10.1134/s0361768823080066 · Cited by 3

HOPBAS10K: A 98 × 98 Pixels CMOS Vision Sensor for Background Subtraction

García-Lesta, D., Cabello, D., Lopez, P., & Brea, V. M. (2024) · IEEE Sensors Journal · doi:10.1109/jsen.2024.3367169 · Cited by 3

Comparing Mask R-CNN backbone architectures for human detection using thermal imaging

Trinh, T. D., Vu, P. C. L. T., & Bao, P. T. (2024) · International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering · doi:10.11591/ijece.v14i4.pp3962-3970 · Cited by 4

Robust Foreground Segmentation in RGBD Data from Complex Scenes Using Adversarial Networks

Sultana, M., Bouwmans, T., Giraldo, J. H., & Jung, S. K. (2021) · Communications in computer and information science · doi:10.1007/978-3-030-81638-4_1 · Cited by 3

Unsupervised inner-point-pairs model for unseen-scene and online moving object detection

Zhao, X., Wang, G., He, Z., Liang, D., Zhang, S., & Tan, J. (2022) · The Visual Computer · doi:10.1007/s00371-022-02417-1 · Cited by 3

Anomaly Detection in Surveillance Video of Natural Environment

Pereira, S. S. L., & Maia, J. E. B. (2021) · International Journal of Computer Applications · doi:10.5120/ijca2021921288 · Cited by 3

Comparación multiplaforma de técnicas basadas en visión artificial para detección de personas en espacios abiertos

Rondón, C. V. N., Casadiego, S. A. C., Delgado, B. M., Ibarra, D. G., Mateus, J. J. R., & López, K. C. P. (2020) · Investigación e Innovación en Ingenierías · doi:10.17081/invinno.9.1.3965 · Cited by 3

Vehicles detection and counting based on internet of things technology and video processing techniques

Marzouk, M. A., & Azeem, A. A. E. (2022) · IAES International Journal of Artificial Intelligence · doi:10.11591/ijai.v11.i2.pp405-413 · Cited by 3

Computer Vision Method in Means of Egress Obstruction Detection

Idowu, I. A., Nyarko, K., & Toutsop, O. (2022) · IEEE World AI IoT Congress (AIIoT) · doi:10.1109/aiiot54504.2022.9817354 · Cited by 3

Convolutional Neural Network for Background Removal in Close Range Photogrammetry: Application on Cultural Heritage Artefacts

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