ARSOD-YOLO: Enhancing Small Target Detection for Remote Sensing Images.

Remote sensing images play a vital role in domains including environmental monitoring, agriculture, and autonomous driving. However, the detection of targets in remote sensing images remains a challenging task. This study introduces innovative methods to enhance feature extraction, feature fusion, and model optimization.

A Context-aware Locality Measure for Inlier Pool Enrichment in Stepwise Image Registration.

We present a feature-based image registration method, the stepwise image registration (SIR), with a closed-form solution. Our SIR creates an inlier pool and a candidate pool as the initialization, and then gradually enriches the inlier pool and refines the transformation. In each step, the enriched correspondence exclusively tunes the transformation coefficient within the confirmed inlier pairs, instead of updating the mapping using the complete putative set.