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Vicon Physical Action Data Set Dataset 10 normal and 10 aggressive physical actions that measure the human activity tracked by a 3D tracker. Many parameters recorded by 3D tracker. 3000 Text Classification 2011 [170] [171] T. Theodoridis Daily and Sports Activities Dataset Motor sensor data for 19 daily and sports activities.
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 of the 80 Million Tiny Images dataset from 2008, published in 2009. When the ...
CIFAR-100 Dataset Like CIFAR-10, above, but 100 classes of objects are given. Classes labelled, training set splits created. 60,000 Images Classification 2009 [18] [36] A. Krizhevsky et al. CINIC-10 Dataset A unified contribution of CIFAR-10 and Imagenet with 10 classes, and 3 splits. Larger than CIFAR-10.
Kaggle is a data science competition platform and online community for data scientists and machine learning practitioners under Google LLC.Kaggle enables users to find and publish datasets, explore and build models in a web-based data science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.
All datasets are formatted according to the same format (Brain Imaging Data Structure) and can be accessed via Amazon S3. Human Macroscopic Functional, structural, diffusion MRI, and Magnetoencephalography datasets Healthy and various diseases No [39] Open MEG Archive (OMEGA) Magnetoencephalography, structural MRI datasets, and demographics Human
BioLib is an international encyclopedia of plants, fungi and animals. X X X X X X X X X X Apart from taxonomic system you can visit the gallery, glossary, vernacular names dictionary, database of links and literature, systems of biotopes, discussion forum and several other functions related to biology CITES species database [7]
In 2021, ImageNet-1k was updated by annotating faces appearing in the 997 non-person categories. They found training models on the dataset with these faces blurred caused minimal loss in performance. [31] ImageNetV2 was a new dataset containing three test sets with 10,000 each, constructed by the same methodology as the original ImageNet. [32]
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]