Imad Eddine Toubal

According to our database1, Imad Eddine Toubal authored at least 12 papers between 2020 and 2024.

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Bibliography

2024
DeepFTSG: Multi-stream Asymmetric USE-Net Trellis Encoders with Shared Decoder Feature Fusion Architecture for Video Motion Segmentation.
Int. J. Comput. Vis., 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

Enhancing Lesion Segmentation in the BONBID-HIE Challenge: An Ensemble Strategy.
Proceedings of the AI for Brain Lesion Detection and Trauma Video Action Recognition, 2023

The First Visual Object Tracking Segmentation VOTS2023 Challenge Results.
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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
Multi-Expert Deep Networks for Multi-Disease Detection in Retinal Fundus Images.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

2021
Single View Facial Age Estimation Using Deep Learning with Cascaded Random Forests.
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
Deep Learning Semantic Segmentation for High-Resolution Medical Volumes.
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


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