9 datasets found

Fine-grained image classification is a challenging computer vision task where various species share similar visual appearances, resulting in misclassification if merely based on...

The dataset used in the paper is Stanford Car, a fine-grained image classification dataset.

The Caltech-USCD Birds-200-2011 dataset contains 30,607 images of 200 bird species.

Fine-grained image classification, which aims to distinguish images with subtle distinctions, is a challenging task due to two main issues: lack of sufficient training data for...

Stanford Dogs, Stanford Cars, Oxford 102 Flowers

The Caltech-256 object category dataset is used for the feature extraction step, and the Omniglot dataset is used for the evaluation.

The dataset used in the paper is CUB200-2011, a fine-grained image classification dataset.

Food-101 dataset is a large-scale dataset for food image classification, with 101 classes and over 30,000 images.

Fine-Grained Visual Classification (FGVC) is an important computer vision prob-lem that involves small diversity within the different classes, and often requires expert...