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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 [7] Srinivasan e al, Google Research Visual Genome Images and their description 108,000 images, text Image captioning 2016 [8] R. Krishna et al.
The basic intent of the contrast enhancement technique is to adjust the local contrast in the image so as to bring out the clear regions or objects in the image . Low-contrast images often result from poor or non-uniform lighting conditions, a limited dynamic range of the imaging sensor , or improper settings of the lens aperture.
[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. [17] [18] The images in EMNIST were converted into the same 28x28 pixel format, by the same process, as were the MNIST ...
It has found use in analyzing human response to contrast-detail phantoms. [18] SSIM has also been used on the gradient of images, making it "G-SSIM". G-SSIM is especially useful on blurred images. [19] The modifications above can be combined. For example, 4-G-r* is a combination of 4-SSIM, G-SSIM, and r*.
For the photographic darkroom process, a large-format glass plate negative is contact-copied onto a low-contrast film or plate to create a positive image. However, the positive copy is made with the copy material in contact with the back of the original, rather than emulsion-to-emulsion , so it is blurred.
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 of the 80 Million Tiny Images dataset from 2008, published in 2009. When the dataset was created, students were paid to label all of the images. [5]
For example, if applied to 8-bit image displayed with 8-bit gray-scale palette it will further reduce color depth (number of unique shades of gray) of the image. Histogram equalization will work the best when applied to images with much higher color depth than palette size, like continuous data or 16-bit gray-scale images.
The ImageNet project is a large visual database designed for use in visual object recognition software research. More than 14 million [1] [2] images have been hand-annotated by the project to indicate what objects are pictured and in at least one million of the images, bounding boxes are also provided. [3]