List of datasets in computer vision and image processing information
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List of datasets for machine-learning research
List of datasets in computer vision and image processing
Outline of machine learning
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This is a list of datasets for machine learning research. It is part of the list of datasets for machine-learning research. These datasets consist primarily of images or videos for tasks such as object detection, facial recognition, and multi-label classification.
and 20 Related for: List of datasets in computer vision and image processing information
Computervision tasks include methods for acquiring, processing, analyzing and understanding digital images, and extraction of high-dimensional data from...
parameters were shown to be comparable to vision transformers of similar size on ImageNet and similar image classification tasks. If a multilayer perceptron...
faster computersand big data, has led to achievements in speech recognition, object recognition inimages, image captioning, language translation and world...
A vision transformer (ViT) is a transformer designed for computervision. A ViT breaks down an input image into a series of patches (rather than breaking...
Proximal policy optimization (PPO) is an algorithm in the field of reinforcement learning that trains a computer agent's decision function to accomplish difficult...
its characteristics. Words, phrases, or entire documents, andimages, audio, and other types of data can all be vectorized. These feature vectors may be...
Can It Be? Estimating the Difficulty of Visual Search in an Image". 2016 IEEE Conference on ComputerVisionand Pattern Recognition (CVPR) (PDF). pp. 2157–2166...
used for applications such as computervisionand natural language processing, originally developed by Meta AI and now part of the Linux Foundation umbrella...
Institute of Standards and Technology database) is a large database of handwritten digits that is commonly used for training various imageprocessing systems...
bootstrap, and out-of-bag datasets. Each section below will explain how each dataset is made except for the original dataset. The original dataset is whatever...
as noise, shadowing, and variations in cameras, traditional hard clustering is often unable to reliably perform imageprocessing tasks as stated above...
recognition model developed by Hinton et al, the ReLU used in the 2012 AlexNet computervision model andin the 2015 ResNet model. Aside from their empirical performance...
compute for datasets larger than a couple of thousand examples without parallel processing. Kernel methods owe their name to the use of kernel functions...
Vision transformers adapt the transformer to computervision by breaking down input images as a series of patches, turning them into vectors, and treating...
instead of a flat result. In 1972, Robert F. Ling published a closely related algorithm in "The Theory and Construction of k-Clusters" in The Computer Journal...
copies of existing data. Synthetic Minority Over-sampling Technique (SMOTE) is a method used to address imbalanced datasetsin machine learning. In such...
normalize the range of independent variables or features of data. In data processing, it is also known as data normalization and is generally performed...
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