Scholarlink

To locate and recognize things in a picture or a video is the aim of object recognition. Before the development of deep learning, object recognition required several processes. Many commonplace applications, including security systems, video surveillance systems, self-driving cars, and guides for the blind and visually handicapped, are built on deep learning and object detection. This paper offers a comprehensive review of deep learning-based item identification approaches, covering various object detection methodologies, deep learning-based object recognition frameworks, and specific model attributes. In addition to several other models like VGGNet, ResNet, DenseNet, and AlexNet, this paper also covers the construction and operation of the Convolutional Neural Network (CNN). The underlying history of object detection is also covered in this essay, which focuses on object recognition applications such as face and human detection, weapon recognition, and pedestrian identification. A detailed summary is also presented that may help to serve further enhancement in the related domain of research.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

A State-of-the-Art Review of Deep Learning-Based Object Detection Methods and Techniques

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • Chhaya Gupta,
  • Nasib Singh Gill,
  • Preeti Gulia

摘要

To locate and recognize things in a picture or a video is the aim of object recognition. Before the development of deep learning, object recognition required several processes. Many commonplace applications, including security systems, video surveillance systems, self-driving cars, and guides for the blind and visually handicapped, are built on deep learning and object detection. This paper offers a comprehensive review of deep learning-based item identification approaches, covering various object detection methodologies, deep learning-based object recognition frameworks, and specific model attributes. In addition to several other models like VGGNet, ResNet, DenseNet, and AlexNet, this paper also covers the construction and operation of the Convolutional Neural Network (CNN). The underlying history of object detection is also covered in this essay, which focuses on object recognition applications such as face and human detection, weapon recognition, and pedestrian identification. A detailed summary is also presented that may help to serve further enhancement in the related domain of research.