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Xception: Deep Learning with Depthwise Separable Convolutions
Xception: A deep neural network architecture for image classification and segmentation. -
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
Segnet: A deep convolutional encoder-decoder architecture for image segmentation. -
Berkeley Segmentation Database
The Berkeley Segmentation Database is a collection of images with manually annotated segmentations. -
Spleen dataset
The dataset used for training and testing the proposed deep co-training method for semi-supervised image segmentation. -
SUSTech-SYSU dataset for Automated Exudate Detection and Diabetic Retinopathy...
SUSTech-SYSU dataset is a collection of images of diabetic retinopathy. -
Retinal Lesions
Retinal Lesions dataset is a collection of images of retinal lesions. -
Indian Diabetic Retinopathy Image Dataset (IDRiD)
The dataset used for the proposed Concept-Centric Visual Turing Test (VTT) framework for evaluating MIC methods. -
MMWHS Dataset
The MMWHS dataset, a dataset for multi-modality whole heart segmentation. -
Caltech Silhouettes dataset
The dataset used in the paper is a subset of the Caltech Silhouettes database, consisting of 11 images with 42 to 59 pixels in each class. -
Public Benchmark for Cardiac Substructure Segmentation
A public benchmark for the cardiac substructure segmentation task, which consists of 20 unpaired CT and 20 MRI images from 40 patients. -
QuakeCity dataset
The QuakeCity dataset, which was released as part of the 2nd International Competition for Structural Health Monitoring contains simulated UAV-captured images of buildings that... -
Digital brain phantom simulated dataset
Digital brain phantom simulated dataset for image segmentation -
Cooperative Image Segmentation
The dataset used in the paper is a distributed image segmentation problem, where each agent has access to only a portion of the entire image. -
HorseSeg dataset
The HorseSeg dataset is a large-scale image segmentation dataset -
Combined Approach for Image Segmentation
The dataset used in this paper for image segmentation is a grayscale image. -
AVIRIS Indian Pines, AVIRIS Salinas, AVIRIS University of Pavia
The dataset used for hyperspectral image classification, consisting of three images: Indian Pines, Salinas, and University of Pavia. -
Microsoft COCO 2014 and 2017
Microsoft COCO 2014 and 2017 datasets for object detection, segmentation, and captioning -
Medical Image Segmentation dataset
The dataset contains images of medical images and corresponding labels.
