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RAWPED is a dataset for detection of pedestrians in the context of railways. The dataset is labeled box-wise. 26000 Images Object recognition and classification 2020 [70] [71] Tugce Toprak, Burak Belenlioglu, Burak Aydın, Cuneyt Guzelis, M. Alper Selver OSDaR23 OSDaR23 is a multi-sensory dataset for detection of objects in the context of railways.
A dataset for NLP and climate change media researchers The dataset is made up of a number of data artifacts (JSON, JSONL & CSV text files & SQLite database) Climate news DB, Project's GitHub repository [394] ADGEfficiency Climatext Climatext is a dataset for sentence-based climate change topic detection. HF dataset [395] University of Zurich ...
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.
It is best to use a download manager such as GetRight so you can resume downloading the file even if your computer crashes or is shut down during the download. Download XAMPPLITE from (you must get the 1.5.0 version for it to work). Make sure to pick the file whose filename ends with .exe
The CIFAR-10 dataset (Canadian Institute For Advanced Research) is a collection of images that are commonly used to train machine learning and computer vision algorithms. It is one of the most widely used datasets for machine learning research. [1] [2] The CIFAR-10 dataset contains 60,000 32x32 color images in 10 different classes. [3]
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.
The Iris flower data set or Fisher's Iris data set is a multivariate data set used and made famous by the British statistician and biologist Ronald Fisher in his 1936 paper The use of multiple measurements in taxonomic problems as an example of linear discriminant analysis. [1]
The file is simple. A flat file can be a plain text file (e.g. csv, txt or tsv), or a binary file. Relationships can be inferred from the data in the database, but the database format itself does not make those relationships explicit. The term has generally implied a small database, but very large databases can also be flat.