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Very Deep Convolutional Networks for Large-Scale Image Recognition
The dataset consists of 60,000 images of objects in 200 categories, with 300 images per category. -
CARLA dataset
The dataset used in the paper is a collection of images and corresponding affordances (pedestrian hazard, vehicle hazard, red traffic light, and relative heading angle) for... -
MIT-Adobe FiveK
The MIT-Adobe FiveK dataset, a large-scale dataset for image segmentation and object detection. -
Prabhakar’s dataset
A fast, scalable, and reliable deghosting method for extreme exposure fusion. -
Tursun’s dataset
An objective deghosting quality metric for HDR images. -
Kalantari’s dataset
Deep high dynamic range imaging of dynamic scenes. -
Hu’s dataset
Frame high dynamic range photography. -
FlyingThings3D dataset
The FlyingThings3D dataset is a benchmark for stereo matching, consisting of a large collection of images and corresponding disparity maps. -
Decision Support System for Detection and Classification of Skin Cancer using...
Skin Cancer detection and classification using CNN -
NAO robot database
The NAO robot database published in [1] which includes images taken in various game situations and under different illumination conditions. -
Data Level Lottery Ticket Hypothesis for Vision Transformers
The conventional lottery ticket hypothesis (LTH) claims that there exists a sparse subnetwork within a dense neural network and a proper random initial-ization method called the... -
Internal Head and Neck CT Dataset
Internal head and neck CT scans for normal organ segmentation -
Computational Anatomy Dataset
Head and neck CT scans for normal organ segmentation -
Focal Vision Transformers
Vision transformers have achieved encouraging progress in various computer vision tasks. A common belief is that this is attributed to the competence of self-attention in... -
Zebra2Horse Dataset
The zebra2horse dataset is a widely used benchmark dataset for image-to-image translation tasks in the field of computer vision. -
RIO-10 dataset
The RIO-10 dataset contains 10 real indoor environments with varying lighting conditions, camera positions, and object arrangements. -
ImageNet1K and ImageNet21K for image classification, and MS COCO for object d...
The dataset used in the paper is ImageNet1K and ImageNet21K for image classification, and MS COCO for object detection. -
ImageNet trained PyTorch models under various simple image transformations
ImageNet trained PyTorch models are evaluated under various simple image transformations. -
PowerLinear Activation Functions with application to the first layer of CNNs
Convolutional neural networks (CNNs) have become the state-of-the-art tool for dealing with unsolved problems in computer vision and image processing.
