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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. -
Delaunay Triangulation
The dataset used in the paper is a Delaunay Triangulation with n vertices, where n ranges from 1000 to 10000. -
Random Geometric Graphs
The dataset is a random geometric graph with vertex set [n] based on n i.i.d. random vectors X1,..., Xn drawn from an unknown density f on Rd. -
U2-Net: A Bayesian U-Net Model for Photoreceptor Layer Segmentation in Pathol...
A dataset of pathological OCT scans for photoreceptor layer segmentation -
BraTS and MVTec AD datasets
The dataset used in the paper is a combination of medical images, including T1, T2, and Flair MRI scans from BraTS, and images from MVTec AD. -
Modular U-Net for automated segmentation of X-ray tomography images in compos...
A reinterpretation of the U-Net architecture as a modularized structure was proposed as a solution to scale up the segmentation of such images. -
MS COCO dataset
The MS COCO dataset is a large benchmark for image captioning, containing 328K images with 5 caption descriptions each. -
ImageNet, ImageNet ReaL, ImageNet V2, etc.
The dataset used in the paper is not explicitly described. However, it is mentioned that the authors used various benchmarks such as ImageNet, ImageNet ReaL, ImageNet V2, etc. -
Synthetic Data
The dataset used in the paper is a synthetic dataset for off-policy contextual bandits, with contexts x ∈ X, a finite set of actions A, and bounded real rewards r ∈ A → [0, 1]. -
Stanford 2D3DS dataset
The Stanford 2D3DS dataset contains omni-directional images. -
PASCAL-5i and COCO-20i
PASCAL-5i and COCO-20i are datasets used for evaluation of few-shot segmentation. -
ISPRS Vaihingen and ISPRS Potsdam datasets
High-resolution remote sensing images
