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20202026
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cs.CV2026

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation

Marina Chagas Bulach Gapski, Vinicius Atsushi Sato Kawai, Gustavo Rosseto Leticio +3

Feature extraction involves the identification and extraction of salient characteristics or patterns, including edges, textures, shapes, and color attributes. Contemporary feature…

cs.CV2026

CrackForward: Context-Aware Severity Stage Crack Synthesis for Data Augmentation

Nassim Sadallah, Mohand Saïd Allili

Reliable crack detection and segmentation are vital for structural health monitoring, yet the scarcity of well-annotated data constitutes a major challenge. To address this limitat…

cs.CV2025

Saliency-Guided Deep Learning for Bridge Defect Detection in Drone Imagery

Loucif Hebbache, Dariush Amirkhani, Mohand Saïd Allili +1

Anomaly object detection and classification are one of the main challenging tasks in computer vision and pattern recognition. In this paper, we propose a new method to automaticall…

cs.CV2025

Unmasking Facial DeepFakes: A Robust Multiview Detection Framework for Natural Images

Sami Belguesmia, Mohand Saïd Allili, Assia Hamadene

DeepFake technology has advanced significantly in recent years, enabling the creation of highly realistic synthetic face images. Existing DeepFake detection methods often struggle…

cs.CV2024

Texture image retrieval using a classification and contourlet-based features

Asal Rouhafzay, Nadia Baaziz, Mohand Said Allili

In this paper, we propose a new framework for improving Content Based Image Retrieval (CBIR) for texture images. This is achieved by using a new image representation based on the R…

cs.CV2020

Efficient embedding network for 3D brain tumor segmentation

Hicham Messaoudi, Ahror Belaid, Mohamed Lamine Allaoui +5

3D medical image processing with deep learning greatly suffers from a lack of data. Thus, studies carried out in this field are limited compared to works related to 2D natural imag…