Scene classification (NWPU-RESISC45, UC Merced, AID)

data category: Remote sensing benchmarks · 0 papers in the last 7 days

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Hyperspectral and aerial image collections used to compare classification and detection methods.

Names searched for: NWPU-RESISC45, RESISC45, UC Merced Land Use, UCMerced, Aerial Image Dataset

Tasks, access and usage conditions#

Mention counts below measure name matches in tracked papers, not benchmark quality or downloads. A family count can cover multiple datasets; it is not a separate count for each comparison row. Choose a task and version first, preserve evaluation splits, and follow the linked release terms. The site's content license does not replace the datasets' own terms.

Dataset comparison: tasks, access and usage conditions
Dataset / version	Task and evaluation	Access and preparation	Usage conditions
NWPU-RESISC45	RGB remote-sensing scene classification: 31,500 images, 45 scene classes. Evaluation: Report mean and variability across splits. Randomly held-out images test a different question from geographic transfer.	Official source / documentation Use the dataset link on the creator’s page; record the train/test proportion, seed and repetitions.	Cite the creator’s benchmark paper and verify the dataset-specific terms; nearby datasets on the same website may use different licenses.
UC Merced Land Use	21-class overhead-image scene classification. Evaluation: Disclose train/test proportions, seeds and augmentation; small sample size makes split variation important.	Official source / documentation Use the university’s original land-use release and preserve class labels; confirm the current availability of its archive.	Check the source-imagery and release terms; this guide does not infer a license from a repackaged copy.
AID	Aerial scene classification with 10,000 images in 30 classes. Evaluation: Report accuracy with repeated splits; this is image-level scene classification, not DOTA box detection.	Official source / documentation Use the authors’ download links and record split proportion, seed and image preprocessing.	The release requests the benchmark citation. Verify source-image and dataset permissions before redistribution or commercial reuse.

Guide updated 2026-11-05.

Key findings#

From Nov 2023 to Oct 2026, 39 archived papers mentioned Scene classification (NWPU-RESISC45, UC Merced, AID) in their title, abstract or keywords (the search of earlier months' full texts is still under way), most of them in Mar 2025 (4).
No paper of the tracked journals mentioned Scene classification (NWPU-RESISC45, UC Merced, AID) in the last 30 days (2026-10-07 to 2026-11-05).
From 2017 to 2026 (so far), Scene classification (NWPU-RESISC45, UC Merced, AID) was mentioned in 48 papers in the tracked journals, most of them in AI (47) and operations research (1).
11 of them were published in 2025, against 0 in 2017.
Since 2023, the institutions with the most of these papers were Wuhan University (7), Shanghai Jiao Tong University (4) and Nanyang Technological University (3).
The journals publishing most of them were IEEE Transactions on Pattern Analysis and Machine Intelligence (8), Neural Computing and Applications (8) and Pattern Recognition (5).
The most-cited of them is “Vision-Language Models for Vision Tasks: A Survey” (IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024), with 998 citations.
Papers use Scene classification (NWPU-RESISC45, UC Merced, AID) most often with ImageNet (25), CIFAR-10 / CIFAR-100 (12) and MS COCO (8); it has 18 partners in the code and data network, in the group around ImageNet, CIFAR-10 / CIFAR-100, MNIST / Fashion-MNIST.

Mentions over 36 months#

Papers mentioning it by publication month, Nov 2023 to Oct 2026 (titles, abstracts and keywords; the full texts of earlier months are still being searched)
Trend	Nov 23–Oct 24	Nov 24–Oct 25	Nov 25–Oct 26	36 months
	15	11	13	39

Papers per year#

20172026 (so far)

Papers per publication year and category
Category	2020	2021	2022	2023	2024	2025	2026 (so far)
AI	2	2	1	6	13	11	12
Operations Research	0	0	0	0	1	0	0
All categories	2	2	1	6	14	11	12

Where the papers come from#

Journals with the most papers, since 2023
#	Journal	Papers
1	IEEE Transactions on Pattern Analysis and Machine Intelligence	8
2	Neural Computing and Applications	8
3	Pattern Recognition	5
4	Artificial Intelligence Review	3
5	International Journal of Computer Vision	3
6	IEEE Transactions on Neural Networks and Learning Systems	3
7	Applied Intelligence	2
8	Knowledge-Based Systems	2
9	Artificial Intelligence	1
10	Pattern Recognition Letters	1

Institutions with the most papers, since 2023
#	Institution	Papers
1	Wuhan University	7
2	Shanghai Jiao Tong University	4
3	Nanyang Technological University	3
4	Aberystwyth University	2
5	Chinese Academy of Sciences	2
6	Huazhong University of Science and Technology	2
7	Lancaster University	2
8	RIKEN	2
9	Southeast University	2
10	The University of Tokyo	2

Countries with the most papers, since 2023
#	Country	Papers
1	China	21
2	United States	7
3	Singapore	4
4	United Kingdom	3
5	Brazil	2
6	Egypt	2
7	Spain	2
8	France	2
9	Italy	2
10	Japan	2

Keywords with the most papers, since 2023
#	Keyword	Papers
1	computational efficiency	5
2	remote sensing image classification	5
3	remote sensing images	5
4	convolutional neural networks	4
5	few-shot learning	4
6	explainable AI	3
7	knowledge distillation	3
8	model compression	3
9	parameter-efficient fine-tuning	3
10	vision-language models	3

Most-cited papers#

Most-cited papers since 2017
#	Citations	Per month	Title	Journal	Published	Authors
1	998	30.9	Vision-Language Models for Vision Tasks: A Survey	IEEE Transactions on Pattern Analysis and Machine Intelligence	2024-02-26	Jingyi Zhang, Jiaxing Huang, Sheng Jin et al.
2	271	10.4	A comprehensive review of model compression techniques in machine learning	Applied Intelligence	2024-09-02	Pierre V. Dantas, Waldir Sabino da Silva, Lucas Carvalho Cordeiro et al.
3	224	5.4	Review of deep learning methods for remote sensing satellite images classification: experimental survey and comparative analysis	Journal Of Big Data	2023-06-02	Adekanmi Adeyinka Adegun, Serestina Viriri, Jules‐Raymond Tapamo
4	195	2.6	C-CNN: Contourlet Convolutional Neural Networks	IEEE Transactions on Neural Networks and Learning Systems	2020-07-21	Mengkun Liu, Licheng Jiao, Xu Liu et al.
5	182	2.7	Deep Feature Aggregation Framework Driven by Graph Convolutional Network for Scene Classification in Remote Sensing	IEEE Transactions on Neural Networks and Learning Systems	2021-04-15	Kejie Xu, Hong Bing Huang, Peifang Deng et al.

Archive counts by publication year: a paper counts when its title, abstract or keywords name the dataset, or when OpenAlex's full-text search finds it there (searched for the last 30 days' papers and, by a pass over the past years, for older ones). Names added to the list later are looked for in older papers as the archive is read again.

Used together with#

Papers use Scene classification (NWPU-RESISC45, UC Merced, AID) most often with ImageNet (25), CIFAR-10 / CIFAR-100 (12) and MS COCO (8); it has 18 partners in the code and data network, in the group around ImageNet, CIFAR-10 / CIFAR-100, MNIST / Fashion-MNIST. The whole network →

What papers use Scene classification (NWPU-RESISC45, UC Merced, AID) together with (at least 3 papers; lift 1 = chance)
Used with	Type	Papers using both	Lift
ImageNet	Dataset	25	10.6
CIFAR-10 / CIFAR-100	Dataset	12	8.6
MS COCO	Dataset	8	8.6
SVHN	Dataset	8	38.1
Sentinel / Copernicus	Dataset	7	25.3
Caltech-101 / 256	Dataset	6	40.4
Kaggle	Dataset	6	10.4
DOTA / xView	Dataset	5	81.7
Fine-grained benchmarks (CUB-200, Stanford Cars, Oxford Flowers)	Dataset	5	21.8
Landsat	Dataset	5	26.5
MNIST / Fashion-MNIST	Dataset	5	4.5
Hugging Face Hub	Dataset	4	8.5

Cite this page

Scholar4AI. (2026). Scene classification (NWPU-RESISC45, UC Merced, AID). Journal and Conference Research Rankings. Retrieved November 5, 2026, from https://scholar4ai.com/datasets/scene-classification-nwpu-resisc45-uc-merced-aid

@misc{scholar4ai-datasets-scene-classification-nwpu-resisc45-uc-merced-aid,
  author = {{Scholar4AI}},
  title = {Scene classification (NWPU-RESISC45, UC Merced, AID)},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/datasets/scene-classification-nwpu-resisc45-uc-merced-aid}},
  urldate = {2026-11-05},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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