6 papers
Advanced Unsupervised Learning: A Comprehensive Overview of Multi-View Clustering Techniques
Abdelmalik Moujahid, Fadi Dornaika
Machine learning techniques face numerous challenges to achieve optimal performance. These include computational constraints, the limitations of single-view learning algorithms and…
Local and Global Context-and-Object-part-Aware Superpixel-based Data Augmentation for Deep Visual Recognition
Fadi Dornaika, Danyang Sun
Cutmix-based data augmentation, which uses a cut-and-paste strategy, has shown remarkable generalization capabilities in deep learning. However, existing methods primarily consider…
HSMix: Hard and Soft Mixing Data Augmentation for Medical Image Segmentation
Danyang Sun, Fadi Dornaika, Nagore Barrena
Due to the high cost of annotation or the rarity of some diseases, medical image segmentation is often limited by data scarcity and the resulting overfitting problem. Self-supervis…
Edge Artificial Intelligence: A Systematic Review of Evolution, Taxonomic Frameworks, and Future Horizons
Mohamad Abou Ali, Fadi Dornaika
Edge Artificial Intelligence (Edge AI) embeds intelligence directly into devices at the network edge, enabling real-time processing with improved privacy and reduced latency by pro…
Comprehensive Benchmarking of YOLOv11 Architectures for Scalable and Granular Peripheral Blood Cell Detection
Mohamad Abou Ali, Mariam Abdulfattah, Baraah Al Hussein +4
Manual peripheral blood smear (PBS) analysis is labor intensive and subjective. While deep learning offers a promising alternative, a systematic evaluation of state of the art mode…
Extremely Fine-Grained Visual Classification over Resembling Glyphs in the Wild
Fares Bougourzi, Fadi Dornaika, Chongsheng Zhang
Text recognition in the wild is an important technique for digital maps and urban scene understanding, in which the natural resembling properties between glyphs is one of the major…