… -of-the-art approach for object detection as supported by the … the R-CNN algorithm to deal
with the small object detection … “objectness” for small objects in order to obtain a small set of …

… ] to solve the detection problems of small objects and achieved good performance. … R-CNN,
this paper proposes an improved method based on Faster R-CNN for small object detection. …

… R-CNN to the task of company logo detection. Motivated by the weak performance of Faster
R-CNN on small object … behavior for a wide range of object sizes. Additionally, we look at the …

… However, directly applying the Faster R-CNN to the small remote sensing objects usually …
to modify Faster R-CNN for the task of small object detection in optical remote sensing images. …

… RCNN, in which we add a deconvolution layer in the base network of Faster R-CNN to
recover small object … good results in the small object detection of remote sensing images. Our …

… small part of the images. In this paper, we aim at improving the accuracy of small object
detection. … of object detection algorithms on small object detection. Secondly, we improve Faster …

… oriented object detection systems. This work proposes an effective and simple ori… object
detection framework, termed Oriented R-CNN, which is a general two-stage oriented detector …

… Robust Faster R-CNN for detecting objects in multi-label images. Robust Faster R-CNN
employs a … In general, the problem associated with small object detection is actually a problem …

… of the R-CNN model, fast R-CNN model is proposed [8]. Compared with the R-CNN model
… candidate region, the Fast R-CNN model only extracts once for the detected image, and then …

… to detect tiny objects, we comprehensively analyzed why the detected performance drops
drastically with tiny objects … Align brings little improvement to the FPN Faster R-CNN baseline. …