34701 manually segmented 384x384 patches with cloud masks, Landsat 8 imagery (R,G,B,NIR; 30 m res. Building footprints (Rio de Janeiro), 3/8band Worldview-3 imagery (0.5m res. Stream Visdrone-DET while training ML models. Also comes with binary classification tags for each subscene, describing what surface types, cloud types, etc. Denmark: 293 crop/vegetation catgeories, 600k parcels. FloodNet (University of Maryland, Jun 2021) 2020. Open AI Challenge: Tanzania (WeRobotics & Wordlbank, Nov 2018) Tree position, tree species and crown parameters, hyperspectral (1m res.) & RGB imagery (0.25m res. 2020, SEN12MS-CR-TS - Ebel et al. Corresponding imagery from drone, satellite and ground camera of 1,652 university buildings, Paper: Zheng et al.
), 4 global cities, 1 holdout city for leaderboard evaluation, APLS metric, baseline model, SEN12MS (TUM, Jun 2019)
label: tensor representing the object detected. 6 land cover categories, 400k 28x28 pixel chips, 4-band RGBNIR aerial imagery (1m res.) It is designed to promote the integration of vision and drones. 2017, Deepsat: SAT-4/SAT-6 airborne datasets (Louisiana State University, 2015) Agricultural Crop Cover Classification Challenge (CrowdANALYTIX, Jul 2018) ), raster mask labels in in run-length encoding format, Kaggle kernels. BioCAS 2015 will comprise an excellent combination of invited talks and tutorials from pioneers in the field as well as peer-reviewed special and regular sessions plus live demonstrations. | Privacy | Terms. Tools. Citation: Alemohammad S.H., et al., 2020 and blog post, LandCover.ai: Dataset for Automatic Mapping of Buildings, Woodlands and Water from Aerial Imagery (Boguszewski, A., et al., May 2020) Worldview-3 (8-band, 0.35cm res.) road-flooded, ). 20k 256 x 256 pixel chips, 2 categories oil-palm and other, annotator confidence score. 21 land cover categories from agricultural to parkinglot, 100 chips per class, aerial imagery (0.30m res.
Paper: Chiu et al. 2016, LoveDA (Wuhan University, Oct 2021) : Human-verified labels on approximately 237K segments with 1000 classes are collected from the validation set of the YouTube-8M dataset. Visdrone-DET testing split comprises 548 images. 180,748 corresponding image triplets containing Sentinel-1 (VV&VH), Sentinel-2 (all bands, cloud-free), and MODIS-derived land cover maps (IGBP, LCCS, 17 classes, 500m res.). ), 122 locations, 22 countries) plane annotations & properties and satellite images. The AISKYEYE team at Tianjin University Lab of Machine Learning and Data Mining has gathered the data for the VisDrone2019 benchmark dataset. Please see these fantastic ressources for more recent datasets: Airbus Oil Storage Detection (Airbus, Mar 2021) ), Paper: Xu et al. We use variants to distinguish between results evaluated on : Search over 585 datasets for machine learning. 790k building footprints from Openstreetmap (2 label quality categories), aerial imagery (0.03-0.2m resolution, RGB, 11k 1024x1024 chips, COG format), 10 cities in Africa. 2020 Outcome Part B: Lian et al. 2017, EuroSAT (DFK, Aug 2017) Drone imagery (0.1m res., RGB), labels (7 land cover catageories: building, clutter, vegetation, water, ground, car) & elevation data, baseline model implementation. 4 cloud categories (cloud, thin cloud, cloud shadows, clear), 96 Landsat 8 scenes (30m res. 12.6mil (Canada) & 125.2mil (USA) & 17.9mil (Uganda/Tanzania) & 11.3mil (Australia) building footprints, GeoJSON format, delineation based on Bing imagery using ResNet34 architecture.
Weekly Planetscope time-series (3m res.) ), covering cities in 30 countries, Paper: Helber et al.
2020, xView 2018 Detection Challenge (DIUx, Jul 2018) 2018, SpaceNet 3: Road Network Detection (CosmiQ Works, Radiant Solutions, Feb 2018) ), 80 1kx1k px. res) timeseries for 2 years, 100 locations around the globe, for building footprint evolution & address propagation. 2018, Urban 3D Challenge (USSOCOM, Dec 2017) 20 land cover categories by fusing three data sources: Multispectral LiDAR, Hyperspectral (1m), RGB imagery (0.05m res. 513 cropped subscenes (1022x1022 pixels) taken randomly from entire 2018 Sentinel-2 archive. ), SpaceNet Challenge Asset Library. Paper: It is now read-only. its variants. Synthetic (630k planes, 50k images) and real (14.7k planes, 253 Worldview-3 images (0.3m res. Agriculture-Vision Database & CVPR 2020 challenge (UIUC,
add Spacenet Round 6 - Multi-Sensor All Weather Mapping, Recent additions and ongoing competitions. BigEarthNet: Large-Scale Sentinel-2 Benchmark (TU Berlin, Jan 2019) In fact, TrajNet is a superset of diverse datasets that requires to train on four families of trajectories, namely 1) BIWI Hotel (orthogonal birds eye flight view, moving people), 2) Crowds UCY (3 datasets, tilted birds eye view, camera mounted on building or utility poles, moving people), 3) MOT PETS (multisensor, different human activities) and 4) Stanford Drone Dataset (8 scenes, high orthogonal birds eye flight view, different agents as people, cars etc. compact high-rise, 7 rural e.g. The Street View House Numbers (SVHN) Dataset. 10 land cover categories from industrial to permanent crop, 27k 64x64 pixel chips, 3/16 band Sentinel-2 satellite imagery (10m res. : (Common Objects in Context) is a large-scale dataset object detection, segmentation, and captioning dataset. of provided building footprints (22,553), RGB UAV imagery (4cm res., 7 areas in 3 Carribbean countries), SpaceNet 5: Automated Road Network Extraction & Route Travel Time Estimation (CosmiQ Works, Maxar, Intel, AWS, Sep 2019)
If you're a dataset owner and do not want your dataset to be included in this library, please get in touch through a. . 8000 km of roads in 5 city aois, 3/8band Worldview-3 imagery (0.3m res. All bands resampled to 20m, stored as numpy arrays. 2 categories ship and iceberg, 2-band HH/HV polarization SAR imagery, Kaggle kernels, Functional Map of the World Challenge (IARPA, Dec 2017)
3647 drone images from 50 scenes, 39991 objects with 6 categories (human, wind/sup-board, boat, bouy, sailboat, kayak), Darknet YOLO format, Paper: Authors: Gasienica-Jzkowy et al. 2020, IEEE Data Fusion Contest 2018 (IEEE, Mar 2018) 2019, Statoil/C-CORE Iceberg Classifier Challenge (Statoil/C-CORE, Jan 2018) Paper: Rahnemoonfar et al., 2021, PASTIS : Panoptic Agricultural Satellite TIme Series (IGN, July 2021) 2019 Outcome Part A: Kunwar et al. Netherlands: 294 crop/vegetation catgeories, 780k parcels, CrowdAI Mapping Challenge (Humanity & Inclusion NGO, May 2018)
IEEE Data Fusion Contest 2019 (IEEE, Mar 2019) Highly accurate street lane markings (12 categories e.g. Predict the chronological order of images taken at the same locations over 5 days, Kaggle kernels. SpaceNet: Multi-Sensor All-Weather Mapping (CosmiQ Works, Capella Space, Maxar, AWS, Intel, Feb 2020) extracted from the 2009 National Agriculture Imagery Program (NAIP), Paper: Basu et al. Microsoft BuildingFootprints Canada & USA & Uganda/Tanzania & Australia (Microsoft, Mar 2019) 131k ships, 104k train / 88k test image chips, satellite imagery (1.5m res. 2015, UC Merced Land Use Dataset (UC Merced, Oct 2010) Visdrone-DET Dataset Citation Information. It is your responsibility to determine whether you have permission to use the datasets under their license. The TrajNet Challenge represents a large multi-scenario forecasting benchmark. for 5.7 km2 of Munich, Germany. 5987 image chips (Google Earth), 7 landcover categories, 166768 labels, 3 cities in China. ), multiple AOIs in Tonga, NIST DSE Plant Identification with NEON Remote Sensing Data (inria.fr, Oct 2017) Visdrone-DET validation split comprises 1580 images. Draper Satellite Image Chronology (Draper, Jun 2016) ), Kaggle kernels, SPARCS: S2 Cloud Validation data (USGS, 2016) Oil storage tank annotations, 98 worldwide images (SPOT, 1.2m res., 2560px). Airbus Aircraft Detection (Airbus, Mar 2021) Train a model on Visdrone-DET dataset with PyTorch in Python, dataloader = ds.pytorch(num_workers=0, batch_size=4, shuffle=False), Train a model on Visdrone-DET dataset with TensorFlow in Python, https://github.com/VisDrone/VisDrone-Dataset, Zhu, Pengfei and Wen, Longyin and Du, Dawei and Bian, Xiao and Fan, Heng and Hu, Qinghua and Ling, Haibin: Detection and Tracking Meet Drones Challenge, Zhu, Pengfei and Wen, Longyin and Du, Dawei and Bian, Xiao and Fan, Heng and Hu, Qinghua and Ling, Haibin, Visdrone-DET Dataset Licensing Information. 2018. 2021. 550k building footprints & 4 damage scale categories, 20 global locations and 7 disaster types (wildfire, landslides, dam collapses, volcanic eruptions, earthquakes/tsunamis, wind, flooding), Worldview-3 imagery (0.3m res. RarePlanes: Synthetic Data Takes Flight (CosmiQ Works, A.I.Reverie, June 2020)
), 12 biomes with 8 scenes each, Paper: Foga et al. ), 5 cities, ISPRS Potsdam 2D Semantic Labeling Contest (ISPRS) Newest datasets at the top of each category (Instance segmentation, object detection, semantic segmentation, scene classification, other). Paper: SEN12MS-CR - Ebel et al. All data upsampled to 10m res., georeferenced, covering all continents and meterological seasons, Paper: Schmitt et al. 2019. Multi-View Stereo 3D Mapping Challenge (IARPA, Nov 2016) 126k building footprints (Atlanta), 27 WorldView 2 images (0.3m res.) Monthly building footprints and Planet imagery (4m. 124,422 Agricultural parcels, 2,433 Sentinel-2 image chip timeseries, France, panoptic labels (instance index + semantic label for each pixel). ), Rotterdam, Netherlands. We are excited to hear from the following at the BioCAS 2015 Gala Dinner Forum, "The most important problems to be tackled by the BioCAS community": Join the following at the BioCAS 2015 Parallel Workshop, "Lessons Learned Along the Translational Highway": Steve Maschino,Cyberonics, Inc., Intermedics, Jared William Hansen, North Dakota State University, Johanna Neuber, University of Texas at Austin, Muhammad Awais Bin Altaf, Masdar Institute of Science and Technology, Piyakamal Dissanayaka Manamperi, RMIT University, Mami Sakata, Yokohama National University, Elham Shabani Varaki, University of Western Sydney, Mahdi Rasouli, National University of Singapore, A Smart Homecage System with Behavior Analysis and Closed-Loop Optogenetic Stimulation Capacibilities, Yaoyao Jia, Zheyuan Wang, Abdollah Mirbozorgi, Maysam GhovanlooGeorgia Institute of Technology, A 12-Channel Bidirectional Neural Interface Chip with Integrated Channel-Level Feature Extraction and PID Controller for Closed-Loop Operation, Xilin Liu, Milin Zhang, Andrew Richardson, Timothy Lucas, Jan Van der SpiegelUniversity of Pennsylvania, A Wireless Optogenetic Headstage with Multichannel Neural Signal Compression, Gabriel Gagnon-Turcotte, Yoan Lechasseur, (Doric Lenses Inc.), Cyril Bories, Yves De Koninck, Benoit GosselinUniversit Laval, 32k Channels Readout IC for Single Photon Counting Detectors with 75 m Pitch, ENC of 123 e- rms, 9 e- rms Offset Spread and 2% rms Gain Spread, Pawel Grybos, Piotr Kmon, Piotr Maj, Robert SzczygielAGH University of Science and Technology, BioCAS 2015 - Atlanta, Georgia, USA - October 22-24, 2015. ), manual segmentations masks for Buildings, Woodland and Water, Paper: Boguszewski et al., 2020, 95-Cloud: A Cloud Segmentation Dataset (S. Mohajerani et. 2343 image chips (drone imagery), 10 landcover categories (background, water, building flooded, building non-flooded, ), SpaceNet Challenge Asset Library, Paper: Van Etten et al. scattered trees), 400k 32x32 pixel chips covering 42 cities (LCZ42 dataset), Sentinel 1 & Sentinel 2 (both 10m res. ), Paper: Hughes, J.M. buildings, roads, vegetation). & DSM, 38 image patches. This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. for year 2017 with cloud masks, Official Slovenian land use land cover layer as ground truth. 2020. Dedicated to the free and open sharing of raw magnetic resonance imaging (MRI) datasets..
Annual datasets. RoadNet (Wuhan, Oct 2018) ), 6 cities, Paper: Mundhenk et al. Semi-supervised semantic segmentation, 19 cities and surroundings with multi-sensor tiles (VHR Aerial imagery 50cm res., Elevation model) & per pixel labels (contains landcover / landuse classes from UrbanAtlas 2012), Data. Intelinair, CVPR, Jan 2020) 41 orthophotos (9000x9000 px) over Poland, Aerial Imagery (25cm & 50cm res. )., ca.
124,422 Agricultural parcels, 2,433 Sentinel-2 image chip timeseries, France, panoptic labels (instance index + semantic label for each pixel). This repository has been archived by the owner. SpaceNet 7: Multi-Temporal Urban Development Challenge (CosmiQ Works, Planet, Aug 2020) satellite-image-deepl-learning & Trajnet extends substantially the 5-dataset scenario by diversifying the training data, thus stressing the flexibility and generalization one approach has to exhibit when it comes to unseen scenery/situations. We do not host or distribute these datasets, vouch for their quality or fairness, or claim that you have a license to use the datasets.
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