A Comparison Study on Different Crowd Motion Estimation Algorithms Using Matlab. - Ibrahim Kajo; Nidal S. Kamel; Aamir Saeed Malik (DaEng, 2013)

Motion estimation of crowd flow using optical flow techniques: A review. - Ibrahim Kajo; Aamir Saeed Malik; Nidal S. Kamel (ICSPCS, 2015)

An adaptive block-based matching algorithm for crowd motion sequences. - Ibrahim Kajo; Nidal S. Kamel; Aamir Saeed Malik (Multim. Tools Appl., 2018)

SVD-Based Tensor-Completion Technique for Background Initialization. - Ibrahim Kajo; Nidal S. Kamel; Yassine Ruichek; Aamir Saeed Malik (IEEE Trans. Image Process., 2018)

On Visual Periodicity Estimation Using Singular Value Decomposition. - Nidal S. Kamel; Ibrahim Kajo; Yassine Ruichek (J. Math. Imaging Vis., 2019)

Incremental Tensor-Based Completion Method for Detection of Stationary Foreground Objects. - Ibrahim Kajo; Nidal S. Kamel; Yassine Ruichek (IEEE Trans. Circuits Syst. Video Technol., 2019)

Self-Motion-Assisted Tensor Completion Method for Background Initialization in Complex Video Sequences. - Ibrahim Kajo; Nidal S. Kamel; Yassine Ruichek (IEEE Trans. Image Process., 2020)

Frequency-Aware SVD Decomposition and its Application to Color Magnification and Motion Denoising. - Ibrahim Kajo; Nidal S. Kamel; Yassine Ruichek; Abdul Rahman Al-Ahdal (IEEE Access, 2021)

Tensor-Based Approach for Background-Foreground Separation in Maritime Sequences. - Ibrahim Kajo; Nidal S. Kamel; Yassine Ruichek (IEEE Trans. Intell. Transp. Syst., 2021)

Coarse-to-fine SVD-GAN based framework for enhanced frame synthesis. - Mohamed Kas; Ibrahim Kajo; Yassine Ruichek (Eng. Appl. Artif. Intell., 2022)

Spatiotemporal CNN with Pyramid Bottleneck Blocks: Application to eye blinking detection. - Salah Eddine Bekhouche; Ibrahim Kajo; Yassine Ruichek; Fadi Dornaika (Neural Networks, 2022)

History Based Incremental Singular Value Decomposition for Background Initialization and Foreground Segmentation. - Ibrahim Kajo; Yassine Ruichek; Nidal S. Kamel (CIARP, 2023)

Tensor based completion meets adversarial learning: A win-win solution for change detection on unseen videos. - Ibrahim Kajo; Mohamed Kas; Yassine Ruichek; Nidal S. Kamel (Comput. Vis. Image Underst., 2023)

Learning by competing: Competitive multi-generator based adversarial learning. - Ibrahim Kajo; Mohamed Kas; Abderrazak Chahi; Yassine Ruichek (Appl. Soft Comput., 2023)

End-to-end Inception-Unet based Generative Adversarial Networks for Snow and Rain Removals. - Ibrahim Kajo; Mohamed Kas; Yassine Ruichek (CoRR, 2024)

No-reference quality evaluation of realistic hazy images via singular value decomposition. - Ibrahim Kajo; Abderrazak Chahi; Mohamed Kas; Yassine Ruichek (Neurocomputing, 2024)

EigenGAN: An SVD subspace-based learning for image generation using Conditional GAN. - Mohamed Kas; Abderrazak Chahi; Ibrahim Kajo; Yassine Ruichek (Knowl. Based Syst., 2024)

DLL-GAN: Degradation-level-based learnable adversarial loss for image enhancement. - Mohamed Kas; Abderrazak Chahi; Ibrahim Kajo; Yassine Ruichek (Expert Syst. Appl., 2024)

MFGAN: towards a generic multi-kernel filter based adversarial generator for image restoration. - Abderrazak Chahi; Mohamed Kas; Ibrahim Kajo; Yassine Ruichek (Int. J. Mach. Learn. Cybern., 2024)

Subspace-guided GAN for realistic single-image dehazing scenarios. - Ibrahim Kajo; Mohamed Kas; Abderrazak Chahi; Yassine Ruichek (Neural Comput. Appl., 2024)

R2GAN: Enhancing unseen image fusion with reconstruction-guided generative adversarial network. - Abderrazak Chahi; Mohamed Kas; Ibrahim Kajo; Yassine Ruichek (Appl. Intell., 2025)