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Wikipedia-based Image Text Dataset 37.5 million image-text examples with 11.5 million unique images across 108 Wikipedia languages. 11,500,000 image, caption Pretraining, image captioning 2021 [11] Srinivasan e al, Google Research Visual Genome Images and their description 108,000 images, text Image captioning 2016 [12] R. Krishna et al.
Synthetic Fundus Dataset [261] Photorealistic retinal images and vessel segmentations. Public domain. 2500 images with 1500*1152 pixels useful for segmentation and classification of veins and arteries on a single background. 2500 Images Classification, Segmentation 2020 [262] C. Valenti et al. EEG Database
Extended MNIST (EMNIST) is a newer dataset developed and released by NIST to be the (final) successor to MNIST. [15] [16] MNIST included images only of handwritten digits. EMNIST includes all the images from NIST Special Database 19 (SD 19), which is a large database of 814,255 handwritten uppercase and lower case letters and digits.
Computer algorithms for recognizing objects in photos often learn by example. CIFAR-10 is a set of images that can be used to teach a computer how to recognize objects. Since the images in CIFAR-10 are low-resolution (32x32), this dataset can allow researchers to quickly try different algorithms to see what works. CIFAR-10 is a labeled subset ...
The iris data set is widely used as a beginner's dataset for machine learning purposes. The dataset is included in R base and Python in the machine learning library scikit-learn, so that users can access it without having to find a source for it. Several versions of the dataset have been published. [8]
In other words, object categorization from image search is one component of the system. OPTIMOL, for example, uses a classifier trained on images collected during previous iterations to select additional images for the returned dataset. Examples of CBIR methods that model object categories from image search are: Fergus et al., 2004 [5]
scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...
The 80 Million Tiny Images dataset was retired from use by its creators in 2020, [5] after a paper by researchers Abeba Birhane and Vinay Prabhu found that some of the labeling of several publicly available image datasets, including 80 Million Tiny Images, contained racist and misogynistic slurs which were causing models trained on them to exhibit racial and sexual bias.