Aug 2026· Machine Vision and Applications· Vol 37· 0 citations· 60 references
Computer Science
TL;DR
Experiments demonstrate that the proposed self-supervised machine vision framework effectively segments camouflaged traces in low-quality, unlabeled outdoor images captured by a mobile robot, outperforming existing COD models in adaptation speed and segmentation accuracy on a challenging custom rescue dataset.
Evaluating multi-source training strategies at the data, pixel, object, and training levels demonstrates that synthetic data effectiveness is not inherent but conditional on how it is generated, structured, and integrated relative to the target architecture and available real data, providing practical guidance for scal...
Rúben Freitas, V. Aguiar, Noel Ferreira et al.· IEEE Access· 0 citations
A context-gated dynamic perception framework that treats small-object feature degradation as a coupled problem of representation, fusion, and prediction and indicates a practical accuracy-efficiency trade-off for dense aerial small-object perception.
Guang-Jun Gao, Ruibing Xie· Pattern Analysis and Applica...· 0 citations
AD-YOLO is presented, a dual-level framework that tackles pseudo-label noise and limited multi-scale adaptability when applied to semi-supervised object detection frameworks from both the detector architecture and the SSOD pipeline.
Jie Long· Engineering Research Express· 0 citations
The onboard-capable version of the YOLOv11 instance segmentation architecture with airborne infrared imagery of wildfires is trained using training labels obtained from a separate self-supervised learning framework, demonstrating the feasibility of self-supervised machine learning for creating training labels.
Lily McKenna, Nicholas LaHaye, Hugo K. Lee et al.· Journal of Applied Remote Se...· 0 citations
Multimodal fusion methods have shown great potential in remote sensing image analysis, but existing approaches rely heavily on massive amounts of annotated data. This is not only costly and time-consuming but also prone to subjective bias. To address this issue, we propose a category-prior-based self-supervised framewo...
Jia-Hang Liu, Jian Cui, Mao-yin Guo et al.· IEEE Transactions on Geoscie...· 0 citations
Comprehensive comparisons with CNN-, Transformer- and prevailing Mamba-based approaches verify the advantages of SCI-Mamba in visual authenticity, color fidelity and inference speed, and provides a practical low-light enhancement solution for close-proximity non-cooperative space operations.
Yiyong Sun, W. Shan, Shijun Wei et al.· 0 citations
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