New Foggy Object Detecting Model
This addresses the problem of inaccurate object recognition in foggy conditions for applications like autonomous driving or surveillance, but appears incremental as it builds on existing detection frameworks.
The paper tackled object detection in reduced visibility by introducing a two-staged architecture for region identification and object detection, achieving notable improvements in accuracy and detection time over existing techniques.
Object detection in reduced visibility has become a prominent research area. The existing techniques are not accurate enough in recognizing objects under such circumstances. This paper introduces a new foggy object detection method through a two-staged architecture of region identification from input images and detecting objects in such regions. The paper confirms notable improvements of the proposed method's accuracy and detection time over existing techniques.