dataset quality assessmentimbalanced datasetsclassificationsegmentationgenerative adversarial networkstraining data generationThis article addresses the issue of imbalanced datasets in satellite image segmentation problems, where machine learning models often neglect minority classes in favor of majority ones. We ...
We trained Unet on 4 channel input: 3 channels were used for RGB input and the 4th channel was used for hill shade data. Weights for the first 3 channels are initialized from VGG 16 model pre-trained on theImageNetdataset. We were leaving the 4th channel initialized with zeroes — further...
iSAID: Large-scale Dataset for Object Detection in Aerial Images(IIAI & Wuhan University, Dec 2019) 15 categories from plane to bridge, 188k instances, object instances and segmentation masks (MS COCO format), Google Earth & JL-1 image chips, Faster-RCNN baseline model (MXNet),devkit, Aca...
Dataset-Converters-> a conversion toolset between different object detection and instance segmentation annotation formats Voxel51 FiftyOne-> tool for building high quality datasets and computer vision models. Visualise labels, evaluate model predictions, explore scenarios of interest, identify failure modes,...
Observing and precisely defining change, in this context, requires both time-series data and pixel-wise segmentations. To that end, we propose the DynamicEarthNet dataset that consists of daily, multi-spectral satellite observations of 75 selected areas of interest distributed over the globe with ...
Semantic Segmentation-Based Building Footprint Extraction Using Very High-Resolution Satellite Images and Multi-Source GIS Data satellite images using the SpaceNet building dataset provided in the DeepGlobe Satellite Challenge of IEEE Conference on Computer Vision and Pattern Recognition ... W Li,C He,...
In this work, we present SAT-MTB-SOS, the first frame-by-frame and pixel-level annotated benchmark dataset for satellite video single object segmentation. SAT-MTB-SOS contains 113 high-quality video sequences with a total of 13,500 frames, covering five categories of typical targets in ...
In this study, two types of satellite image dataset were used, Landsat-7 ETM+ and Quickbird, representing moderate- and high-spatial resolution imagery respectively. To achieve the research objectives, a methodology comprising three stages of activity was developed. The first stage specified local ...
AU-AIR dataset-> a multi-modal UAV dataset for object detection. ERA-> A Dataset and Deep Learning Benchmark for Event Recognition in Aerial Videos. Aerial Maritime Drone Dataset The Synthinel-1 dataset: a collection of high resolution synthetic overhead imagery for building segmentation ...
uav drone satellite pytorch dataset remote-sensing awesome-list place-recognition image-retrieval cross-view cvusa geo-localization multi-source-benchmark cvact gem-pooling Updated Sep 18, 2024 Python kscottz / PythonFromSpace Star 452 Code Issues Pull requests Python Examples for Remote Sensing...