14 datasets found

The DenseNet dataset is a dataset for image recognition on handwritten digits composed of 60,000 training data and 10,000 test images.

The dataset consists of 60,000 images of objects in 200 categories, with 300 images per category.

The dataset used in this paper is the VGG Network E, a deep convolutional neural network for image recognition.

Deep Image: Scaling up image recognition

The ImageNet dataset is a large-scale image database that contains over 14 million images, each labeled with one of 21,841 categories.

A dataset of images of holy places (Kaaba, Zamzam, Maqam Ibrahim) for training a deep learning model.

RoadTracer is an automatic recognition method of road network system, called RoadTracer. RoadTracer can generate a road map on the ground surface from aerial photograph data.

Training neural networks on image datasets generally require extensive experimentation to find the optimal learning rate regime.

The dataset used in the paper is the Imagenet dataset, which is a large annotated dataset of images used for image classification tasks.

The dataset used for training and validation of the proposed approach to combine semantic segmentation and dense outlier detection.

Large scale datasets [18, 17, 27, 6] boosted text conditional image generation quality. However, in some domains it could be difficult to make such datasets and usually it could...

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...

The CIFAR-10 dataset consists of 60,000 training images and 10,000 test images. Each image is a 32×32 color image.

Large scale datasets [18, 17, 27, 6] boosted text conditional image generation quality. However, in some domains it could be difficult to make such datasets and usually it could...