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Found 7 papers, 2 papers with code
Urban feature analysis from aerial remote sensing imagery using self-supervised and semi-supervised computer vision
Analysis of overhead imagery using computer vision is a problem that has received considerable attention in academic literature.
Self-Supervision, Remote Sensing and Abstraction: Representation Learning Across 3 Million Locations
However, the performance of such methods on remote sensing imagery domains remains under-explored.
Identifying safe intersection design through unsupervised feature extraction from satellite imagery
The World Health Organization has listed the design of safer intersections as a key intervention to reduce global road trauma.
Real-time monitoring of driver drowsiness on mobile platforms using 3D neural networks
Phone applications reduce the need for specialised hardware and hence, enable a cost-effective roll-out of the technology across the driving population.
The 'Paris-end' of town? Urban typology through machine learning
A (novel) neural network-based framework is trained with imagery from the largest 1692 cities in the world and the resulting models are used to compare within-city locations from Melbourne and Sydney to determine the closest connections between these areas and their international comparators.
Sky pixel detection in outdoor imagery using an adaptive algorithm and machine learning
To address this problem, we present a new sky pixel detection system demonstrated to produce accurate results using a wide range of outdoor imagery types.
Streetscape augmentation using generative adversarial networks: insights related to health and wellbeing
Deep learning using neural networks has provided advances in image style transfer, merging the content of one image (e. g., a photo) with the style of another (e. g., a painting).
