Imad Eddine Toubal
Orcid: 0000-0003-1754-0823
According to our database1,
Imad Eddine Toubal
authored at least 15 papers
between 2020 and 2025.
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Bibliography
2025
HQ-SMem: Video Segmentation and Tracking Using Memory Efficient Object Embedding With Selective Update and Self-Supervised Distillation Feedback.
CoRR, July, 2025
Evaluating the Reliability of ChatGPT for Health-Related Questions: A Systematic Review.
Informatics, 2025
2024
DeepFTSG: Multi-stream Asymmetric USE-Net Trellis Encoders with Shared Decoder Feature Fusion Architecture for Video Motion Segmentation.
Int. J. Comput. Vis., 2024
Proceedings of the Computer Vision - ECCV 2024 Workshops, 2024
Modeling Collaborator: Enabling Subjective Vision Classification with Minimal Human Effort via LLM Tool-Use.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024
2023
Fusion of Deep and Local Features Using Random Forests for Neonatal HIE Segmentation.
Proceedings of the AI for Brain Lesion Detection and Trauma Video Action Recognition, 2023
Proceedings of the AI for Brain Lesion Detection and Trauma Video Action Recognition, 2023
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023
Real-Time Helmet Violation Detection in AI City Challenge 2023 with Genetic Algorithm-Enhanced YOLOv5.
Proceedings of the 52nd IEEE Applied Imagery Pattern Recognition Workshop, 2023
Marker and Motion Guided Deep Networks for Cell Segmentation and Detection Using Weakly Supervised Microscopy Data.
Proceedings of the 52nd IEEE Applied Imagery Pattern Recognition Workshop, 2023
2022
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022
2021
Proceedings of the Computer Analysis of Images and Patterns, 2021
Extending U-Net Network for Improved Nuclei Instance Segmentation Accuracy in Histopathology Images.
Proceedings of the 50th IEEE Applied Imagery Pattern Recognition Workshop, 2021
2020
Proceedings of the 49th IEEE Applied Imagery Pattern Recognition Workshop, 2020
Deepfake Video Detection Based on Spatial, Spectral, and Temporal Inconsistencies Using Multimodal Deep Learning.
Proceedings of the 49th IEEE Applied Imagery Pattern Recognition Workshop, 2020