SYSTEMS AND METHODS FOR TRAINING GENERATIVE CONTRADICTORY NETWORKS AND USE OF TRAINED GENERATIVE CONTRADICTORY NETWORKS
Patent Information
- Authority / Receiving Office
- DE · DE
- Patent Type
- Patents
- Current Assignee / Owner
- COSMO ARTIFICIAL INTELLIGENCE AI LTD
- Filing Date
- 2019-06-11
- Publication Date
- 2026-05-06
AI Technical Summary
Existing object detection systems in medical imaging, such as endoscopy, struggle with inaccurate feature detection, reliance on manually annotated training sets, difficulty in differentiating false positives from true positives, and delays in real-time analysis, leading to inefficiencies and potential misdiagnosis.
A computer-implemented system using generative adversarial networks (GANs) for training neural networks to enhance object detection, incorporating a two-phase training loop with a perception branch for initial detection and a generative-adversarial branch for refining detections, enabling real-time differentiation between true and false positives.
The system provides improved accuracy and reduced false positives in medical image analysis, allowing for real-time detection and classification of abnormalities, enhancing diagnostic precision.