Computer vision has emerged as a promising technology with numerous applications in
healthcare. This systematic review provides an overview of advancements and challenges …

The safety and reliability of autonomous driving depends on the precision and efficiency of
object detection systems. In this paper, a refined adaptation of the YOLO architecture (WGS …

As deep learning technology has progressed, automated medical image analysis is
becoming ever more crucial in clinical diagnosis. However, due to the diversity and …

Inconsistent illumination across imaging instruments poses significant challenges for
accurate cell detection and analysis. Conventional methods (eg histogram equalization and …

Microscopic examination of cells is essential for biological research and clinical diagnostics.
However traditional manual detection methods are both time-consuming and labor …

The detection of pests and diseases in crops is currently a hot topic. The complexity of pest
and disease object in the field, combined with inconsistent features across different levels …

Detection of small-scale objects is an emerging research area with substantial potential for
growth and significant practical relevance in the domain of object identification. The issue of …

In order to solve the problems of low efficiency, poor accuracy, and outdated technology in
strawberry disease detection technology, this paper proposes an improved YOLOv7 …

Исследованы возможности применения алгоритмов компьютерного зрения для
распознавания клеток крови на биомедицинских изображениях. В качестве основного …

Defect detection in industrial environments, especially in steel tube manufacturing, is critical
to ensuring product integrity and safety. Traditional methods often have problems with …