A Study of Object Detection Based on Weakly Supervised Learning

Guangyao Wang

doi:10.62051/ijcsit.v2n1.50

Authors

Guangyao Wang

DOI:

https://doi.org/10.62051/ijcsit.v2n1.50

Keywords:

Weakly Supervised Learning; Object Detection; Detect the Model

Abstract

Object detection is one of the important research contents in the field of computer vision. At present, the classical object detection methods can be divided into two categories: fully supervised-based target detection and weakly supervised-based target detection. Since the fully supervised object detection model requires a large number of training data with category labels and target bounding boxes, and such labeled data is difficult to obtain, it is of great significance to explore the weakly supervised object detection method that only needs category label data.

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