|
--- |
|
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](https://ieeexplore.ieee.org/iel7/36/7880748/07827088.pdf) |
|
- **Paper** [High-Resolution Remote Sensing Image Retrieval Based on CNNs from a Dimensional Perspective](https://www.mdpi.com/209338) |
|
- **Split** Validation |
|
|
|
## Split Information |
|
|
|
This HuggingFace dataset repository contains just the Validation split. |
|
|
|
### Licensing Information |
|
|
|
[Free for education, research and commercial use.](https://github.com/RSIA-LIESMARS-WHU/RSD46-WHU) |
|
|
|
## Citation Information |
|
|
|
[Accurate Object Localization in Remote Sensing Images Based on Convolutional Neural Networks](https://ieeexplore.ieee.org/iel7/36/7880748/07827088.pdf) |
|
|
|
[High-Resolution Remote Sensing Image Retrieval Based on CNNs from a Dimensional Perspective](https://www.mdpi.com/209338) |
|
|
|
``` |
|
@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 |
|
} |
|
``` |