ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2010.01202
  4. Cited By
Background Adaptive Faster R-CNN for Semi-Supervised Convolutional
  Object Detection of Threats in X-Ray Images

Background Adaptive Faster R-CNN for Semi-Supervised Convolutional Object Detection of Threats in X-Ray Images

2 October 2020
J. Sigman
Gregory P. Spell
Kevin J Liang
Lawrence Carin
    ObjD
ArXivPDFHTML

Papers citing "Background Adaptive Faster R-CNN for Semi-Supervised Convolutional Object Detection of Threats in X-Ray Images"

2 / 2 papers shown
Title
Object Detection as a Positive-Unlabeled Problem
Object Detection as a Positive-Unlabeled Problem
Yuewei Yang
Kevin J Liang
Lawrence Carin
19
37
0
11 Feb 2020
Towards Automatic Threat Detection: A Survey of Advances of Deep
  Learning within X-ray Security Imaging
Towards Automatic Threat Detection: A Survey of Advances of Deep Learning within X-ray Security Imaging
S. Akçay
T. Breckon
31
156
0
05 Jan 2020
1