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Segmenting satellite images of earth : determining which parts are roads. pythoncomputer-visionjupyter-notebookconvolutional-neural-networksroad-segmentation UpdatedMar 26, 2017 Python Star9 Aerial Image segmentation using different EfficientNet based backbone encoders with UNet on Massachusetts Building and ...
This data article provides details for the RDD2020 dataset comprising 26,336 road images from India, Japan, and the Czech Republic with more than 31,000 instances of road damage. The dataset captures four types of road damage: longitudinal cracks, transverse cracks, alligator cracks, and potholes...
THE ENGINE, H10s NUMBER 105 HAD RECENTLY BEEN EQUIPPED WITH A STOKER AND LARGER TENDER. THE HACK IS A PENNSYLVANIA RAILROAD N6B WOOD CABIN CAR. OLIVET TOWER WAS CLOSED IN 1950 WHEN STREET CARS WERE TAKEN OFF FLUSHING AVENUE. THE BUILDING AND SIDING WERE THE WELBILT COMPANY, STOVE AND OVEN...
Alberto F. De Souza, in Expert Systems with Applications, 2021 3.3 Road mapping The mapping techniques presented above can be used to map unstructured environments and make it possible the operation of self-driving cars in any kind of flat terrain. However, for autonomous operation in roads and...
Many of these applications involve real-time prediction on mobile platforms such as cars, drones and various kinds of robots. Real-time setup is challenging due to extraordinary computational complexity involved. Many previous works address the challenge with custom lightweight architectures which ...
Road safety is still one of the major issues worldwide, given that annually approximately 1.3 million people die in road crashes, with an additional 20 to 50 million people injured [1]. In general, the state of road safety is considered to be the result of the interaction between three mai...