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In this paper, we propose a method specifically aimed at improving small birddetection for the Small Object Detection Challenge for Spotting Birds 2023.Utilizing YOLOv7 model with test-time augmentation, our approach involvesincreasing the input resolution, incorporating multiscale inference,considering flipped images during the inference process, and employing weightedboxes fusion to merge detection results. We rigorously explore the impact ofeach technique on detection performance. Experimental results demonstratesignificant improvements in detection accuracy. Our method achieved a top scorein the Development category, with a public AP of 0.732 and a private AP of27.2, both at IoU=0.5.

Small Bird Detection using YOLOv7 with Test-Time Augmentation