An Attention Selection System Based on Neural Network and Its Application in Tracking Objects

2006 ◽  
pp. 404-410 ◽  
Author(s):  
Chenlei Guo ◽  
Liming Zhang
Keyword(s):  
Neural Network ◽  
Selection System ◽  
Attention Selection ◽  
Tracking Objects

scholarly journals Detection and tracking people in real-time with YOLO object detector

2020 ◽  
pp. 69-75
Author(s):  
Aziza Srazhdinova ◽  
Asel’ Ahmetova ◽  
Sunvar Anvarov
Keyword(s):  
Neural Network ◽  
Real Time ◽  
Preliminary Analysis ◽  
Model Output ◽  
Detection And Tracking ◽  
Python Programming Language ◽  
Large Program ◽  
The University ◽  
Python Programming ◽  
Tracking Objects

In this article, we wrote not a large program to solve tasks for detection and tracking objects in real-time. The program was written in Python programming language. For object detection, a convolutional neural network was used with YOLOV3 architecture. A preliminary analysis was carried out of several variations of YOLO with CNN models. In the article, we justify why we want to use YOLO, and what it is and how to use and process the model output. We will also present the code in the form of a flowchart and as a result of the program's performance, we will show a picture of the program's operation in real-time, which was launched at one of the live lectures at the University.

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