Any computer vision application development starts off by acquiring images and data, then
preprocessing and pattern recognition steps to perform a task. When the acquired images …

Accurately estimating the number of objects in a single image is a challenging yet
meaningful task and has been applied in many applications such as urban planning and …

In this paper, an object detection and recognition method based on improved YOLOv5 is
proposed for application on unmanned aerial vehicle (UAV) aerial images. Firstly, we …

Crowd counting in aerial images presents unique challenges due to varying altitudes,
angles, and cluttered backgrounds. Additionally, the small size of targets, often occupying …

Object counting, which aims to count the accurate number of object instances in images, has
been attracting more and more attention. However, challenges such as large-scale variation …

The task of crowd counting is extremely challenging due to complicated difficulties,
especially the huge variation in vision scale. Previous works tend to adopt a naive …

Single image crowd counting is a challenging computer vision problem with wide
applications in public safety, city planning, traffic management, etc. With the recent …

Remote sensing object counting (RSOC) is finding applications in many fields. Global
regression is a long-ignored method for object counting, though it needs much less manual …

Modeling context information is critical for crowd counting and desntiy estimation. Current
prevailing fully-convolutional network (FCN) based crowd counting methods cannot …

People Counting in images is a worthwhile task as it is widely used for public safety,
emergency people planning, intelligent crowd flow, and countless other reasons. Counting …