metadata
dataset_info:
features:
- name: label
sequence:
class_label:
names:
'0': airplane
'1': bare soil
'2': buildings
'3': cars
'4': chaparral
'5': court
'6': dock
'7': field
'8': grass
'9': mobile home
'10': pavement
'11': sand
'12': sea
'13': ship
'14': tanks
'15': trees
'16': water
- name: image
dtype: image
splits:
- name: train
num_bytes: 438859816.5
num_examples: 2100
download_size: 416309630
dataset_size: 438859816.5
license: other
Dataset Card for "UC_Merced_LandUse_MultiLabel"
Dataset Description
- Paper: Bag-of-visual-words and spatial extensions for land-use classification
- Paper: Multilabel Remote Sensing Image Retrieval Using a Semisupervised Graph-Theoretic Method
Licensing Information
Public Domain; “Map services and data available from U.S. Geological Survey, National Geospatial Program.”
Citation Information
Imagery:
Bag-of-visual-words and spatial extensions for land-use classification
Multilabels:
Multilabel Remote Sensing Image Retrieval Using a Semisupervised Graph-Theoretic Method
@inproceedings{yang2010bag,
title = {Bag-of-visual-words and spatial extensions for land-use classification},
author = {Yang, Yi and Newsam, Shawn},
year = 2010,
booktitle = {Proceedings of the 18th SIGSPATIAL international conference on advances in geographic information systems},
pages = {270--279}
}
@article{8089668,
title = {Multilabel Remote Sensing Image Retrieval Using a Semisupervised Graph-Theoretic Method},
author = {Chaudhuri, Bindita and Demir, Begüm and Chaudhuri, Subhasis and Bruzzone, Lorenzo},
year = 2018,
journal = {IEEE Transactions on Geoscience and Remote Sensing},
volume = 56,
number = 2,
pages = {1144--1158},
doi = {10.1109/TGRS.2017.2760909}
}