Fast and Accurate Feature-based Region Identification

Abstract

There have been several improvements in object detection and semantic segmentation results in recent years. Baseline systems that drive these advances are Fast/Faster R-CNN, Fully Convolutional Network and recently Mask R-CNN and its variant that has a weight transfer function. Mask R-CNN is the state-of-art. This research extends the application of the state-of-art in object detection and semantic segmentation in drone-based datasets. Existing drone datasets was used to learn semantic segmentation on drone images using Mask R-CNN. This work is the result of my own activity. I have neither given nor received unauthorized assistance on this work.