We present a neural radiance field method for urban-scale semantic and building-level instance segmentation from aerial images by lifting noisy 2D labels to 3D. This is a challenging problem due to two primary reasons. Firstly, objects in urban aerial images exhibit substantial variations in size,...
managed to overcome the data ambiguity problem rooted in the RF streaming data from measuring the spectral values of a field-of-vision of an area that moves over a land, which is never easy to attain high precision. However, it is shown also that in general both evolutionary swarm search ...
Classifying Wheat Hyperspectral Pixels of Healthy Heads and Fusarium Head Blight Disease Using a Deep Neural Network in the Wild Field. Remote Sens. 2018, 10, 395. [Google Scholar] [CrossRef] Chan, C.S.; Anderson, D.T.; Ball, J.E. Comprehensive survey of deep learning in remote sensing...
Relying on the largest receptive field of the FCN network is not sufficient for providing global context, and the largest empirical receptive field is not sufficient for global capture. ParseNet Baseline and ParseNet trained on the VOC2012 test set achieved a 67.3%67.3% and 69.8%69.8% mIOU, ...