Object Detection with Convolutional Neural Networks

2019/12/04 by Kaidong Li, Wenchi Ma, Li, Kaidong +8
Computer Science · Medicine · Neuroscience · #Advanced Neural Network Applications #Brain Tumor Detection and Classification #COVID-19 diagnosis using AI #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #cs.CV

paper · pdf · doi:10.48550/arxiv.1912.01844

arxiv created 2019/12/04 · openalex publication_date 2019/12/04 · arxiv updated 2019/12/05 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

In this chapter, we present a brief overview of the recent development in object detection using convolutional neural networks (CNN). Several classical CNN-based detectors are presented. Some developments are based on the detector architectures, while others are focused on solving certain problems, like model degradation and small-scale object detection. The chapter also presents some performance comparison results of different models on several benchmark datasets. Through the discussion of these models, we hope to give readers a general idea about the developments of CNN-based object detection.

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