kaggle stanford drone datasetrainbow striped blouse

), 122 locations, 22 countries) plane annotations & properties and satellite images. 63 categories from solar farms to shopping malls, 1 million chips, 4/8 band satellite imagery (0.3m res. 21 land cover categories from agricultural to parkinglot, 100 chips per class, aerial imagery (0.30m res. The benchmarks section lists all benchmarks using a given dataset or any of Paper: SEN12MS-CR - Ebel et al. Instead of downloading the Visdrone-DET dataset in Python, you can effortlessly load it in Python via our. 2300 image chips, street geometries with location, shape and estimated travel time, 3/8band Worldview-3 imagery (0.3m res. ), Paper: Mohajerani et al. 34701 manually segmented 384x384 patches with cloud masks, Landsat 8 imagery (R,G,B,NIR; 30 m res. 131k ships, 104k train / 88k test image chips, satellite imagery (1.5m res. Some tasks are inferred based on the benchmarks list. Prediction of presence of oil palm plantations, Planet satellite imagery (3m res. Paper: Chiu et al. ), 4 global cities, 1 holdout city for leaderboard evaluation, APLS metric, baseline model, SEN12MS (TUM, Jun 2019) 2018, SpaceNet 3: Road Network Detection (CosmiQ Works, Radiant Solutions, Feb 2018) Monthly building footprints and Planet imagery (4m. Local climate zone classification, 17 categories (10 urban e.g. 124,422 Agricultural parcels, 2,433 Sentinel-2 image chip timeseries, France, panoptic labels (instance index + semantic label for each pixel). 2016, LoveDA (Wuhan University, Oct 2021) 10 land cover classes, temporal stack of hyperspectral Sentinel-2 imagery (R,G,B,NIR,SWIR1,SWIR2; 10 m res.) 8000 km of roads in 5 city aois, 3/8band Worldview-3 imagery (0.3m res. Visdrone-DET test-dev split comprises 1610 images. - All rights reserved. ), raster mask labels in in run-length encoding format, Kaggle kernels. Classes: water, natural bare ground, artificial bare ground, woody vegetation, cultivated vegetation, (semi) natural vegetation, and permanent snow/ice. buildings, roads, vegetation). 2019, xView 2 Building Damage Asessment Challenge (DIUx, Nov 2019) . Thank you for your contribution to the ML community! ), 12 biomes with 8 scenes each, Paper: Foga et al. from 7-54 degrees off-nadir angle. 6 urban land cover classes, raster mask labels, 4-band RGB-IR aerial imagery (0.05m res.) 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. building flooded, building non-flooded, road-flooded, ..), 2 competition tracks (Binary & semantic flood classification; Object counting & condition recognition), Dynamic EarthNet Challenge (Planet, DLR, TUM, April 2021) This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. Land cover classification based on SEN12MS dataset (see category Semantic Segmentation on this list), low- and high-resolution tracks. ), Kaggle kernels, SPARCS: S2 Cloud Validation data (USGS, 2016) Paper: Rahnemoonfar et al., 2021, PASTIS : Panoptic Agricultural Satellite TIme Series (IGN, July 2021) satellite-image-deepl-learning & 41 orthophotos (9000x9000 px) over Poland, Aerial Imagery (25cm & 50cm res. Multiple landcover labels per chip based on CORINE Land Cover (CLC) 2018, 590,326 chips from Sentinel-2 L2A scenes (125 Sentinel-2 tiles from 10 European countries, 2017/2018), 66 GB archive, Paper: Sumbul et al. Weekly Planetscope time-series (3m res.) 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) On behalf of the BioCAS 2015 Organizing Committee, This site is created, maintained, and managed by Conference Catalysts, LLC. Multiple tracks: Semantic 3D reconstruction, Semantic Stereo, 3D-Point Cloud Classification. 4 cloud categories (cloud, thin cloud, cloud shadows, clear), 96 Landsat 8 scenes (30m res. Awesome_Satellite_Benchmark_Datasets. ), SpaceNet Challenge Asset Library, Paper: Van Etten et al. Paper: Castillo-Navarro et al., 2021, LandCoverNet: A Global Land Cover Classification Training Dataset (Alemohammad S.H., et al., Jul 2020) 2018, TiSeLaC: Time Series Land Cover Classification Challenge (UMR TETIS, Jul 2017) 2 main categories corn and soybeans, Landsat 8 imagery (30m res. ), 51 GB, Cactus Aerial Photos (CONACYT Mexico, Jun 2018) 2017, Inria Aerial Image Labeling (inria.fr) scattered trees), 400k 32x32 pixel chips covering 42 cities (LCZ42 dataset), Sentinel 1 & Sentinel 2 (both 10m res. 2343 UAV images from after Hurricane Harvey, landcover labels (10 categories, e.g. 20 land cover categories by fusing three data sources: Multispectral LiDAR, Hyperspectral (1m), RGB imagery (0.05m res. ), SpaceNet Challenge Asset Library. 155k 128x128px image chips with wind turbines (SPOT, 1.5m res.). 2019. 2014, Biome: L8 Cloud Cover Validation data (USGS, 2016) 6 land cover categories, 400k 28x28 pixel chips, 4-band RGBNIR aerial imagery (1m res.) I look forward to welcoming you to enjoy the conference in Atlanta. 2018. over 2 years, 75 aois, landcover labels (7 categories), 2 competition tracks (Binary land cover classification & multi-class change detection). 32k car bounding boxes, aerial imagery (0.15m res. Papers With Code is a free resource with all data licensed under, An Evaluation of Trajectory Prediction Approaches and Notes on the TrajNet Benchmark. 2019, Statoil/C-CORE Iceberg Classifier Challenge (Statoil/C-CORE, Jan 2018) Manual labeling & active learning, Paper: Baetens et al. : Human-verified labels on approximately 237K segments with 1000 classes are collected from the validation set of the YouTube-8M dataset. | Privacy | Terms. DroneDeploy Segmentation Dataset (DroneDeploy, Dec 2019) 513 cropped subscenes (1022x1022 pixels) taken randomly from entire 2018 Sentinel-2 archive. 2020, IEEE Data Fusion Contest 2018 (IEEE, Mar 2018) 2020, IEEE Data Fusion Contest 2022 (IEEE GRSS, Universit Bretagne-Sud, ONERA, ESA, Jan 2022) : A collection of aerial videos that can be used to train a variety of unmanned autonomous vehicles. Stream Visdrone-DET while training ML models. Netherlands: 294 crop/vegetation catgeories, 780k parcels, CrowdAI Mapping Challenge (Humanity & Inclusion NGO, May 2018) A multi-modal and mono-temporal data set for cloud removal. Airbus Aircraft Detection (Airbus, Mar 2021) 10 land cover categories from crops to vehicle small, 57 1x1km images, 3/16-band Worldview 3 imagery (0.3m-7.5m res. Building footprints (Rio de Janeiro), 3/8band Worldview-3 imagery (0.5m res. We use variants to distinguish between results evaluated on Tree position & 4 tree species, RGB UAV imagery (0.4m/0.8m res. IEEE Data Fusion Contest 2019 (IEEE, Mar 2019) Road network labels, high-res Google Earth imagery, 21 regions, Paper: Liu et al. 2343 image chips (drone imagery), 10 landcover categories (background, water, building flooded, building non-flooded, its variants. AFO - Aerial dataset of floating objects (Gasienica-Jzkowy et al, Jun 2020) Garnot & Landrieu 2021. xView3 Dark Vessel Detection 2021 (xView3 Team, Aug 2021) ), 80 1kx1k px. Agriculture-Vision Database & CVPR 2020 challenge (UIUC, The engaging three-day single-track program, all of which is included in your registration, covers a wide range of topics, including but not limited to: On behalf of the Organizing Committee, I cordially invite you to participate in the 2015 Biomedical Circuits and Systems Conference and contribute to the continued success of this rapidly growing annual event at the intersection of medicine and engineering. The 8-12-value protocol is consistent with the most trajectory forecasting approaches, usually focused on the 5-dataset ETH-univ + ETH-hotel + UCY-zara01 + UCY-zara02 + UCY-univ. 2 categories ship and iceberg, 2-band HH/HV polarization SAR imagery, Kaggle kernels, Functional Map of the World Challenge (IARPA, Dec 2017) SpaceNet 7: Multi-Temporal Urban Development Challenge (CosmiQ Works, Planet, Aug 2020) and ImageNet 6464 are variants of the ImageNet dataset. res) timeseries for 2 years, 100 locations around the globe, for building footprint evolution & address propagation. : (Common Objects in Context) is a large-scale dataset object detection, segmentation, and captioning dataset. 60 categories from helicopter to stadium, 1 million instances, Worldview-3 imagery (0.3m res. ), Rotterdam, Netherlands. 288 video clips composed of 261,908 frames and 10,209 static photos. Since 2018 Microsoft research open data has been collaborating across the research community to collect datasets for a variety of categories. Detection of settlements without electricity, 98 multi-temporal/multi-sensor tiles ( Sentinel-1, Sentinel-2, Landsat-8, VIIRS), per chip & per pixel labels (contains buildings, presence electricity). 2019. boxes: tensor representing bounding box for the object of interest. 20k 256 x 256 pixel chips, 2 categories oil-palm and other, annotator confidence score. Our favorite source for free datasets, collaboration, and competition is Kaggle. This repository has been archived by the owner. compact high-rise, 7 rural e.g. Land cover time series classification (9 categories), Landsat-8 (23 images time series, 10 band features, 30m res. 2018, Open AI Challenge: Aerial Imagery of South Pacific Islands (WeRobotics & Worldbank, May 2018) Draper Satellite Image Chronology (Draper, Jun 2016) 13 land cover categories + 4 cloud condition categories, 4-band (RGB-NIR) satelitte imagery (5m res. Load Visdrone-DET Dataset in Python fast. Highly accurate street lane markings (12 categories e.g. Microsoft BuildingFootprints Canada & USA & Uganda/Tanzania & Australia (Microsoft, Mar 2019) title={Detection and Tracking Meet Drones Challenge}. for 5.7 km2 of Munich, Germany. ), 5 cities, ISPRS Potsdam 2D Semantic Labeling Contest (ISPRS) FloodNet (University of Maryland, Jun 2021) & Hayes D.J. A ChemImage Company - 2022 Innotescus, LLC. Three challenge tracks: Road Extraction, Building Detection, Land cover classification, Paper: Demir et al. author={Zhu, Pengfei and Wen, Longyin and Du, Dawei and Bian, Xiao and Fan, Heng and Hu, Qinghua and Ling, Haibin}. 2019, DEEPGLOBE - 2018 Satellite Challange (CVPR, Apr 2018) 685k building footprints, 3/8band Worldview-3 imagery (0.3m res. ALCD Reference Cloud Masks (CNES, Oct 2018) ), 5 cities, SpaceNet Challenge Asset Library, SpaceNet 1: Building Detection v1 (CosmiQ Works, Radiant Solutions, NVIDIA, Jan 2017) 2020. for year 2017 with cloud masks, Official Slovenian land use land cover layer as ground truth. Stay informed on the latest trending ML papers with code, research developments, libraries, methods, and datasets. Intelinair, CVPR, Jan 2020) ), and density (sparse and crowded scenes). all, Jan 2020) It is your responsibility to determine whether you have permission to use the datasets under their license. ), Paper: Yang & Newsam 2010, SEN12MS-CR & SEN12MS-CR-TS (TUM, Jun 2020) ), COCO data format, baseline models, Paper: Christie 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. Please see these fantastic ressources for more recent datasets: from Copernicus UrbanAtlas 2012), designed for semi-supervised semantic segmentation. 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. 2015, UC Merced Land Use Dataset (UC Merced, Oct 2010) 126k building footprints (Atlanta), 27 WorldView 2 images (0.3m res.) 10 land cover categories from industrial to permanent crop, 27k 64x64 pixel chips, 3/16 band Sentinel-2 satellite imagery (10m res. ), Amazonian rainforest, Kaggle kernels, AID: Aerial Scene Classification (Xia et al., 2017) Airbus Oil Storage Detection (Airbus, Mar 2021) 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. Airbus Ship Detection Challenge (Airbus, Nov 2018) Airbus Wind Turbine Patches (Airbus, Mar 2021) slightly different versions of the same dataset. The challenge consists on predicting 3161 human trajectories, observing for each trajectory 8 consecutive ground-truth values (3.2 seconds) i.e., t7,t6,,t, in world plane coordinates (the so-called world plane Human-Human protocol) and forecasting the following 12 (4.8 seconds), i.e., t+1,,t+12. Open Cities AI Challenge (GFDRR, Mar 2020) . 2017, EuroSAT (DFK, Aug 2017) IEEE Data Fusion Contest 2020 (IEEE & TUM, Mar 2020) 2017, Deepsat: SAT-4/SAT-6 airborne datasets (Louisiana State University, 2015) 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. 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.). 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. Building footprints & 3 building conditions, RGB UAV imagery - Link to data, LPIS agricultural field boundaries Denmark - Netherlands - France Load Visdrone-DET Dataset Training Subset in Python, Load Visdrone-DET Dataset Testing Subset in Python, Load Visdrone-DET Dataset Validation Subset in Python, Load Visdrone-DET Dataset Testing-DEV Subset in Python, How to use Visdrone-DET Dataset with PyTorch and TensorFlow in Python, Additional Information about Visdrone-DET Dataset. All bands resampled to 20m, stored as numpy arrays. The benchmark dataset consists of 288 video clips composed of 261,908 frames and 10,209 static photos collected by several drone-mounted cameras, encompassing a wide variety of features such as location (taken from 14 different cities separated by thousands of kilometres in China), environment (urban and country), objects (pedestrian, automobiles, bicycles, etc. Paper: Xia et al. If you're a dataset owner and do not want your dataset to be included in this library, please get in touch through a. . ), Paper: Xu et al. 48k building footprints (enhanced 3DBAG dataset, building height attributes), Capella Space SAR data (0.5m res., four polarizations) & Worldview-3 imagery (0.3m res. Sentinel-2 Cloud Mask Catalogue (Francis, A., et al., Nov 2020) 2019. )., ca. Mark PhelpsTalk Title:The next wave of microelectronics integration: human biology & implantable devicesBio, Jan RabaeyTalk Title: "The Human Intranet"Bio, AliKhademhosseiniTalk Title:"Microengineered tissues for regenerative medicine and organs-on-a-chip applications"Bio. Drone imagery (0.1m res., RGB), labels (7 land cover catageories: building, clutter, vegetation, water, ground, car) & elevation data, baseline model implementation. 5 sea lion categories, ~ 80k instances, ~ 1k aerial images, Kaggle kernels, Stanford Drone Data (Stanford University, Oct 2016) Denmark: 293 crop/vegetation catgeories, 600k parcels. List of satellite image training datasets with annotations for computer vision and deep learning, The list is now archived. ), Paper: Hughes, J.M. Aircraft bounding boxes, 103 images of worlwide airports (Pleiades, 0.5m res., 2560px). SkyScapes: Urban infrastructure & lane markings (DLR, Nov 2019) 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. SpaceNet 4: Off-Nadir Buildings (CosmiQ Works, DigitalGlobe, Radiant Solutions, AWS, Dec 2018) 2017, Planet: Understanding the Amazon from Space (Planet, Jul 2017) 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, Academic use only, replaces DOTA dataset, Paper: Zamir et al. & RGB imagery (0.25m res. & DSM, 38 image patches. Multi-View Stereo 3D Mapping Challenge (IARPA, Nov 2016) Worldview-3 (8-band, 0.35cm res.) Testing is requested on diverse partitions of BIWI Hotel, Crowds UCY, Stanford Drone Dataset, and is evaluated by a specific server (ground-truth testing data is unavailable for applicants). road-flooded, ). : A great source of data for a wide range of tasks in autonomous driving. Tools. extracted from the 2009 National Agriculture Imagery Program (NAIP), Paper: Basu et al. Visdrone-DET validation split comprises 1580 images. 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. Newest datasets at the top of each category (Instance segmentation, object detection, semantic segmentation, scene classification, other). Paper: Azimi et al. 2016, Cars Overhead With Context (COWC) (Lawrence Livermore National Laboratory, Sep 2016) RoadNet (Wuhan, Oct 2018) Garnot & Landrieu 2021. ), pre-trained baseline model. Version 1.0 of the dataset that contains data across Africa, (20% of the global dataset). The Street View House Numbers (SVHN) Dataset. add Spacenet Round 6 - Multi-Sensor All Weather Mapping, Recent additions and ongoing competitions. Also comes with binary classification tags for each subscene, describing what surface types, cloud types, etc. Includes clear, cloud and cloud-shadow classes. 2021, NEON Tree Crowns Dataset (Weinstein et al., 2020) label: tensor representing the object detected. 2020, xView 2018 Detection Challenge (DIUx, Jul 2018) journal={IEEE Transactions on Pattern Analysis and Machine Intelligence}. Bi-cubicly resampled to same number of pixels in each image to counter courser native resolution with higher off-nadir angles, Paper: Weir et al. 2020, iSAID: Large-scale Dataset for Object Detection in Aerial Images (IIAI & Wuhan University, Dec 2019) Hub users may have access to a variety of publicly available datasets. 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. List of aerial and satellite imagery datasets with annotations for computer vision and deep learning. So2Sat LCZ42 (TUM Munich & DLR, Aug 2018) 2020. Aerial imagery (0.13 m res.) The TrajNet Challenge represents a large multi-scenario forecasting benchmark. Visdrone-DET training split comprises 6471 images. Synthetic (630k planes, 50k images) and real (14.7k planes, 253 Worldview-3 images (0.3m res. 2021. concrete, metal etc.) The AISKYEYE team at Tianjin University Lab of Machine Learning and Data Mining has gathered the data for the VisDrone2019 benchmark dataset. Individual tree crown objects, height&area estimates, 100 million instances, 37 geographic sites across the US, DeepForest Python package, Paper: Weinstein et al. 124,422 Agricultural parcels, 2,433 Sentinel-2 image chip timeseries, France, panoptic labels (instance index + semantic label for each pixel). 5987 image chips (Google Earth), 7 landcover categories, 166768 labels, 3 cities in China. 60 aerial UAV videos over Stanford campus and bounding boxes, 6 classes (Pedestrian, Biker, Skateboarder, Cart, Car, Bus), Paper: Robicquet et al. Open AI Challenge: Tanzania (WeRobotics & Wordlbank, Nov 2018) 157k building footprint masks, RGB orthophotos (0.5m res. IEEE Data Fusion Contest 2021 (IEEE, HP, SolarAid, Data Science Experts, Mar 2021) SpaceNet: Multi-Sensor All-Weather Mapping (CosmiQ Works, Capella Space, Maxar, AWS, Intel, Feb 2020) ), COCO data format, pre-trained Tensorflow and Pytorch baseline models, Paper: Lam et al. RarePlanes: Synthetic Data Takes Flight (CosmiQ Works, A.I.Reverie, June 2020) 45 scene categories from airplane to wetland, 31,500 images (700 per category, 256x256 px), image chips taken from Google Earth (rich image variations in resolution, angle, geography all over the world), Download Link, Paper: Cheng et al. Slovenia Land Cover Classification (Sinergise, Feb 2019) 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. Paper: Wang et al., 2021, FloodNet Challenge (UMBC, Microsoft, Texas A&M, Dewberry, May 2021) Visdrone-DET Dataset Citation Information. Agricultural Pattern Analysis, 21k aerial farmland images (RGB-NIR, USA, 2019 season, 512x512px chips), label masks for 6 field anomaly patterns (Cloud shadow, Double plant, Planter skip, Standing Water, Waterway and Weed cluster). 2019. Paper: Gupta et al. Building footprint masks, RGB aerial imagery (0.3m res. It should be noted that the dataset was gathered utilising a variety of drone platforms (i.e., drones of various types), in a variety of settings, and under a variety of weather and lighting circumstances. Dedicated to the free and open sharing of raw magnetic resonance imaging (MRI) datasets.. : Search over 585 datasets for machine learning. Check our our latest webinar to learn more! Develop a Multi-View Stereo (MVS) 3D mapping algorithm that can convert high-resolution Worldview-3 satellite images to 3D point clouds, 0.2m lidar ground truth data. Paper: Buildings footprints, RGB satellite imagery, COCO data format, SpaceNet 2: Building Detection v2 (CosmiQ Works, Radiant Solutions, NVIDIA, May 2017) Maritime object bounding boxes for 1k Sentinel-1 scenes (VH & VV polarizations), ancillary data (land/ice mask, bathymetry, wind speed, direction, quality). PASTIS: Panoptic Agricultural Satellite TIme Series (IGN, July 2021) Sentinel-1 & Sentinel-2, 2018. 2018, Urban 3D Challenge (USSOCOM, Dec 2017) Annual datasets. On behalf of the Organizing Committee, I am happy to invite you to participate in the IEEE/CAS-EMB Biomedical Circuits and Systems Conference (BioCAS 2015), which will be held on October 22-24, 2015, at the historic Academy of Medicine in Atlanta, Georgia, USA. 2000 very high resolution aerial images over 16 cities in France (50cm res., from IGN BDORTHO), 16 landcover categories (Urban, Industrial, Pastures, Forests, etc. 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. are present. MiniFrance (Universit Bretagne-Sud and ONERA, Jul 2020) ), LiDAR point cloud and canopy height model, NOAA Fisheries Steller Sea Lion Population Count (NOAA, Jun 2017) Visdrone-DET testing split comprises 548 images. Predict the chronological order of images taken at the same locations over 5 days, Kaggle kernels. ), manual segmentations masks for Buildings, Woodland and Water, Paper: Boguszewski et al., 2020, 95-Cloud: A Cloud Segmentation Dataset (S. Mohajerani et. 8 classes (inc. cloud and cloud shadow) for 38 Sentinel-2 scenes (10 m res.). dash line, long line, zebra zone) & urban infrastructure (19 categories e.g. 2019 Outcome Part A: Kunwar et al. Predict building roof type (5 categories, e.g. All data upsampled to 10m res., georeferenced, covering all continents and meterological seasons, Paper: Schmitt et al. Oil storage tank annotations, 98 worldwide images (SPOT, 1.2m res., 2560px). 7 categories (cloud, cloud shadows, cloud shadows over water, water etc. Please feel free to, Talk Title:"Microengineered tissues for regenerative medicine and organs-on-a-chip applications", IEEE CAS Charles Desoer Life Science Systems Student Attendance Grant, Assistive, Rehabilitation, and Quality of Life Technologies, Bio-inspired and Neuromorphic Circuits and Systems, Biofeedback, Electrical Stimulation, and Closed-Loop Systems, Biomedical Imaging Technologies & Image Processing, Innovative Circuits for Medical Applications, Medical Information Systems and Bioinformatics, Wireless and Energy Harvesting/Scavenging Technology. It is designed to promote the integration of vision and drones. Tree position, tree species and crown parameters, hyperspectral (1m res.) 2017, RESISC45 (Northwestern Polytechnical University NWPU, Mar 2017) : Explore datasets by size, category, modality (including X-ray, Ultrasound, Whole Slide Images, CT Scans, ECGs), and more. 175 globally distributed aois. 2019, Open AI Challenge: Caribbean (MathWorks, WeRobotics, Wordlbank, DrivenData, Dec 2019) subset Landsat 8 scenes (30m res. 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) Paper: Shermeyer et al. WiDS Datathon 2019 : Detection of Oil Palm Plantations (Global WiDS Team & West Big Data Innovation Hub, Jan 2019) ), 6 cities, Paper: Mundhenk et al. ), DSM/DTM, 3 cities, SpaceNet Challenge Asset Library, DSTL Satellite Imagery Feature Detection Challenge (Dstl, Feb 2017) ), covering cities in 30 countries, Paper: Helber et al. 2020, SEN12MS-CR-TS - Ebel et al. BigEarthNet: Large-Scale Sentinel-2 Benchmark (TU Berlin, Jan 2019) For example, ImageNet 3232 ), multiple AOIs in Tonga, NIST DSE Plant Identification with NEON Remote Sensing Data (inria.fr, Oct 2017) 2020 Outcome Part B: Lian et al. Paper: University-1652: Drone-based Geolocalization (Image Retrieval) (ACM Multimedia, Oct 2020) Curious about applying augmentation to computer vision datasets? 10000 aerial images within 30 categories (airport, bare land, baseball field, beach, bridge, ) collected from Google Earth imagery. You signed in with another tab or window. ), Reunion island. It is now read-only. satellite imagery, LiDAR (0.80m pulse spacing, ASCII format), semantic labels, urban setting USA, baseline methods provided, Paper: Le Saux et al. 17k aerial photos, 13k cactus, 4k non-actus, Kaggle kernels, Paper: Lpez-Jimnez et al. ), for a total of 11448 trajectories. Agricultural Crop Cover Classification Challenge (CrowdANALYTIX, Jul 2018) 1980 image chips of 256 x 256 pixels in V1.0 spanning 66 tiles of Sentinel-2. The IEEE Biomedical Circuits and Systems Conference (BioCAS) serves as a premier international. ), USDA Cropland Data Layer as ground truth. Corresponding imagery from drone, satellite and ground camera of 1,652 university buildings, Paper: Zheng et al.