In computer vision, significant advances have been made on object detection with the rapid
development of deep convolutional neural networks (CNN). This paper provides a …

Small object detection is an interesting topic in computer vision. With the rapid development
in deep learning, it has drawn attention of several researchers with innovations in …

The data and the algorithm are critical to deep learning-based small object detectors. In this
paper, we rethink the PASCAL-VOC and MS-COCO dataset for small object detection. By …

Detecting small or tiny objects is always a difficult and challenging issue in computer vision.
In this paper, we provide a latest and comprehensive survey of deep learning-based …

The existing object detection algorithm based on the deep convolution neural network
needs to carry out multilevel convolution and pooling operations to the entire image in order …

Small object detection is a challenging problem in computer vision. It has been widely
applied in defense military, transportation, industry, etc. To facilitate in-depth understanding …

Existing object detection literature focuses on detecting a big object covering a large part of
an image. The problem of detecting a small object covering a small part of an image is …

Object detection results have been rapidly improved over a short period of time with the
development of deep convolutional neural networks. Although impressive results have been …

In this paper, an improved algorithm based on Yolo V3 is proposed, which can effectively
improve the accuracy of small target detection. First of all, the feature map acquisition …

Recent studies have achieved great progress on the object detection in terms of accuracy
and speed using convolutional neural networks (CNNs). However, no matter the one-stage …