Object detection is an important area in computer vision, which has had a great impact in
various areas such as medicine. One of the applications in medicine is the detection of …

Aiming at the problem of low recognition accuracy of traditional pest detection methods in
complex environments, this paper introduces dense convolutional network (DenseNet) and …

The necessity to control pests and diseases by biological means using computer and
internet technology instead of pesticides to protect crops is a primary objective of this work …

This paper proposed a method based on Faster R-CNN for detection of human parasite
eggs in stool images. The shapes, and patterns of parasite worm in egg micro images are …

Most object detection methods have low detection accuracy for small and dense objects and
susceptibility to noise interference. In response to these problems, this paper designs an …

Effective prediction of crop pest species and quantities can provide a priori knowledge for
pest control. However, there are many kinds of pests and the color and texture of different …

One of the biggest concerns in the area of public health is caused by human intestinal
parasites, which are found largely in tropical countries. The diagnosis of these parasitic …

The agricultural losses caused by the difficulty of pest detection and unscientific detection
are increasing year by year. The traditional detection and identification methods of …

This research provides a method for recognizing objects in real-time on any model-enabled
device, regardless of the environment. In computer vision, object identification and training …

Object detection algorithm based on deep convolutional neural network has become a
research hotspot in the field of object detection, which includes two-stage object detection …