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ISPRS 2D semantic labeling benchmark (Vaihingen)
The ISPRS 2D semantic labeling benchmark (Vaihingen) dataset is used for evaluating the proposed method. -
LoveDA dataset
The LoveDA dataset consists of 5,987 high-quality optical remote sensing images with a resolution of 0.3 meters per pixel. -
ISPRS Vaihingen dataset
The ISPRS Vaihingen dataset contains 33 high-quality images with topographical information, each with an average resolution of 2494×2064 pixels. -
ISPRS Vaihingen, ISPRS Potsdam, UAVid, and LoveDA datasets
Four widely-used remote sensing datasets are considered for evaluating the efficacy of the proposed approach. Sample images of these datasets are provided in Fig. 5. -
PlanetScope data
PlanetScope data -
Sentinel-2 data
Sentinel-2 data -
Zurich Summer dataset
The Zurich Summer dataset is a benchmark for semantic segmentation in remote sensing. It contains aerial images with 8 urban classes. -
UCM dataset
The UCM dataset is a benchmark for scene classification in remote sensing. It contains aerial images with 21 land-use classes. -
UAE-RS dataset
The UAE-RS dataset is a benchmark for black-box adversarial attacks in remote sensing. It contains adversarial examples generated using the Mixup-Attack and Mixcut-Attack methods. -
Bag-of-visual-words and spatial extensions for land-use classification
Bag-of-visual-words and spatial extensions for land-use classification -
Deep semantic understanding of high resolution remote sensing image
Deep semantic understanding of high resolution remote sensing image -
Exploring models and data for remote sensing image caption generation
Exploring models and data for remote sensing image caption generation -
Remote Sensing Image Captioning
Remote Sensing Image Captioning Dataset (RSICD) and UCM-captions dataset for remote sensing image captioning -
AID dataset
The AID dataset is a benchmark for scene classification in remote sensing. It contains aerial images with 30 scene types. -
Vaihingen dataset
The Vaihingen dataset consists of 1440 scenes with a size of 250×250 pixels. Each scene is a colour-infrared (CIR) true orthophoto and a height grid (digital surface model; DSM)... -
Sentinel 2
Sentinel 2 multispectral data was acquired using Sentinel 2 satellite over Central State farm in Hissar, Haryana (India). -
IRX-1D: A Simple Deep Learning Architecture for Remote Sensing Classifications
Four remote sensing datasets were used for classification with both small and large training samples.
