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Autonomous Vehicle Dataset
The dataset used in the paper is a collection of autonomous vehicle scenarios, where each scenario is represented as a 3x3 grid encoding. The scenarios are encoded using Pauli-X... -
Drawing Recognition dataset
The Drawing Recognition dataset is used to recognize drawings. -
Image Recognition FeedbackLog
Image Recognition FeedbackLog -
MNIST dataset for handwritten digits
The MNIST dataset is a collection of images of handwritten digits, with size n = 70,000 and D = 784. -
Self-Attention Networks
Self-Attention Networks dataset is used for image recognition tasks. -
Inception V2
Inception V2 is a deep neural network for image recognition. It uses a convolutional neural network (CNN) architecture and is trained on a large dataset of images. -
Deep residual learning for image recognition
The ResNet-50 and ResNet-101 are used as the backbone image feature extractor. -
CIFAR10 dataset
The dataset used in this paper is the CIFAR10 dataset, which contains 60,000 32x32 color images in 10 classes, with 6,000 images per class. -
Google Landmark Recognition 2021
Google Landmark Recognition 2021 Competition dataset -
ImageNet with CMA-Search
A dataset of ImageNet images with subtle 3D perspective changes that can break ImageNet-trained classification networks. -
Controlled Rendered Data of Real World Objects
A dataset of complex image data with a fixed, known distribution, generated using a computer graphics pipeline. -
ImageNet Dataset
Object recognition is arguably the most important problem at the heart of computer vision. Recently, Barbu et al. introduced a dataset called ObjectNet which includes objects in... -
CIFAR-10 Dataset
The dataset used in this paper is a neural network, and the authors used it to test the performance of their lookahead pruning method. -
An image is worth 16x16 words: Transformers for image recognition at scale
An image is worth 16x16 words: Transformers for image recognition at scale. -
ImageNet Large Scale Visual Recognition Challenge
A benchmark for low-shot recognition was proposed by Hariharan & Girshick (2017) and consists of a representation learning phase without access to the low-shot classes and a... -
MNIST Dataset
The MNIST dataset (Lecun et al., 1998), which consists of 60,000 gray-scale images of handwritten digits. Each image has an accompanying label in {0, 1,..., 9}, and is stored as...