DEIMv2 is an evolution of the DEIM framework while leveraging the rich features from DINOv3. Our method is designed with various model sizes, from an ultra-light version up to S, M, L, and X, to be ...
Abstract: YOLOv10, known for its efficiency in object detection methods, quickly and accurately detects objects in images. However, when detecting small objects in remote sensing imagery, traditional ...
Dr. James McCaffrey presents a complete end-to-end demonstration of anomaly detection using k-means data clustering, ...
Abstract: Maritime environments often face visibility challenges due to haze which significantly impacts detection models. However, existing maritime object detection algorithms often neglect haze ...
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