README.md

metadata

dataset_info:
  features:
    - name: image
      dtype: image
    - name: label
      dtype:
        class_label:
          names:
            '0': airplane
            '1': airport
            '2': artificial dense forest land
            '3': artificial sparse forest land
            '4': bare land
            '5': basketball court
            '6': blue structured factory building
            '7': building
            '8': construction site
            '9': cross river bridge
            '10': crossroads
            '11': dense tall building
            '12': dock
            '13': fish pond
            '14': footbridge
            '15': graff
            '16': grassland
            '17': irregular farmland
            '18': low scattered building
            '19': medium density scattered building
            '20': medium density structured building
            '21': natural dense forest land
            '22': natural sparse forest land
            '23': oil tank
            '24': overpass
            '25': parking lot
            '26': plastic greenhouse
            '27': playground
            '28': railway
            '29': red structured factory building
            '30': refinery
            '31': regular farmland
            '32': scattered blue roof factory building
            '33': scattered red roof factory building
            '34': sewage plant-type-one
            '35': sewage plant-type-two
            '36': ship
            '37': solar power station
            '38': sparse residential area
            '39': square
            '40': steelworks
            '41': storage land
            '42': tennis court
            '43': thermal power plant
            '44': vegetable plot
            '45': water
  splits:
    - name: train
      num_bytes: 1650045051.96
      num_examples: 17516
  download_size: 2184490825
  dataset_size: 1650045051.96
license: other

Dataset Card for "RSD46-WHU"

Dataset Description

• Paper Accurate Object Localization in Remote Sensing Images Based on Convolutional Neural Networks
• Paper High-Resolution Remote Sensing Image Retrieval Based on CNNs from a Dimensional Perspective
• Split: Validation

Licensing Information

Free for education, research and commercial use.

Citation Information

Accurate Object Localization in Remote Sensing Images Based on Convolutional Neural Networks

High-Resolution Remote Sensing Image Retrieval Based on CNNs from a Dimensional Perspective

@article{long2017accurate,
  title        = {Accurate object localization in remote sensing images based on convolutional neural networks},
  author       = {Long, Yang and Gong, Yiping and Xiao, Zhifeng and Liu, Qing},
  year         = 2017,
  journal      = {IEEE Transactions on Geoscience and Remote Sensing},
  publisher    = {IEEE},
  volume       = 55,
  number       = 5,
  pages        = {2486--2498}
}
@article{xiao2017high,
  title        = {High-resolution remote sensing image retrieval based on CNNs from a dimensional perspective},
  author       = {Xiao, Zhifeng and Long, Yang and Li, Deren and Wei, Chunshan and Tang, Gefu and Liu, Junyi},
  year         = 2017,
  journal      = {Remote Sensing},
  publisher    = {MDPI},
  volume       = 9,
  number       = 7,
  pages        = 725
}