19,997 machine learning datasets
19,997 dataset results
A new data consolidation called Multi-Attributed and Structured Text-to-face (MAST) dataset. The motivation is to have a large corpus of high-quality face images with fine-grained and attribute-focussed annotations. This has the benefits of the attribute oriented approach as well as the semantics in a textual description.
This dataset are about Nafion 112 membrane standard tests and MEA activation tests of PEM fuel cell in various operation condition. Dataset include two general electrochemical analysis method, Polarization and Impedance curves. In this dataset, effect of different pressure of H2/O2 gas, different voltages and various humidity conditions in several steps are considered. Behavior of PEM fuel cell during distinct operation condition tests, activation procedure and different operation condition before and after activation analysis can be concluded from data. In Polarization curves, voltage and power density change as a function of flows of H2/O2 and relative humidity. Resistance of the used equivalent circuit of fuel cell can be calculated from Impedance data. Thus, experimental response of the cell is obvious in the presented data, which is useful in depth analysis, simulation and material performance investigation in PEM fuel cell researches.
Open Set Logo Detection Dataset (OSLD Dataset) is a dataset of eCommerce product images with associated brand logo images. It is released under creative commons (CC BY-NC 4.0) license to promote research in open set logo detection. The dataset can be used only for research purposes. The dataset contains:
N15News is a large-scale multimodal news dataset comprising 200K imagetext pairs and 15 categories, which exceeding the previous news dataset in both the number of categories and samples.
VesselGraph is a dataset of whole-brain vessel graphs based on specific imaging protocols. Specifically, vascular graphs are extracted using a refined graph extraction scheme leveraging the volume rendering engine Voreen and provided in an accessible and adaptable form through the OGB and PyTorch Geometric dataloaders.
CrossedWires is a living dataset of models and hyperparameters that exposes semantic differences between two popular deep learning frameworks: PyTorch and Tensorflow.
A comprehensive dataset, merging all the aforementioned datasets. The newly published dataset represents the benefits of shared dataset feature sets, where the merging of multiple smaller ones is possible. This will eventually lead to a bigger and more universal NIDS datasets containing flows from multiple network setups and different attack settings. An additional label feature identifying the original dataset of each flow. This can be used to compare the same attack scenarios conducted over two or more different test-bed networks. The attack categories have been modified to combine all parent categories. Attacks named DoS attacks-Hulk, DoS attacks-SlowHTTPTest, DoS attacks-GoldenEye and DoS attacks-Slowloris have been renamed to the parent DoS category. Attacks named DDOS attack-LOIC-UDP, DDOS attack-HOIC and DDoS attacks-LOIC-HTTP have been renamed to DDoS. Attacks named FTP-BruteForce, SSH-Bruteforce, Brute Force -Web and Brute Force -XSS have been combined as a brute-force categor
A comprehensive dataset, merging all the aforementioned datasets. The newly published dataset represents the benefits of shared dataset feature sets, where the merging of multiple smaller ones is possible. This will eventually lead to a bigger and more universal NIDS datasets containing flows from multiple network setups and different attack settings. An additional label feature identifying the original dataset of each flow. This can be used to compare the same attack scenarios conducted over two or more different test-bed networks. The attack categories have been modified to combine all parent categories. Attacks named DoS attacks-Hulk, DoS attacks-SlowHTTPTest, DoS attacks-GoldenEye and DoS attacks-Slowloris have been renamed to the parent DoS category. Attacks named DDOS attack-LOIC-UDP, DDOS attack-HOIC and DDoS attacks-LOIC-HTTP have been renamed to DDoS. Attacks named FTP-BruteForce, SSH-Bruteforce, Brute Force -Web and Brute Force -XSS have been combined as a brute-force categor
Arabic Multi Fonts Dataset A multi-word multi-font Arabic word-image dataset.
PhotoMatte85 contains 85 protrait images. The dataset is donated to us by a third-party commercial company. The footage are shot with professional studio lighting and the subjects are in standard portrait posing. We provide the alpha matte and foreground images extracted from the green screen photos. Due to license issue, we will not release the other 13K images used in training.
CICFlowMeter format of the datasets are made up of 83 features.
The Manually Annotated Sub-Corpus (MASC) consists of approximately 500,000 words of contemporary American English written and spoken data drawn from the Open American National Corpus (OANC).
Raw responses of ~10,000 people to a simple survey of creative habits. The numeric responses are an ordinal scale 1-5 for questions that ask about 2 contrasting creative habits/preferences along a given habit dimension. The endpoints of the scale are in the name of the column. The Discipline field is a 'check all that apply' question. These tags were mapped to 3 broad disciplines in the paper. See 'CreativeStyle_Responses_Tagged_Cleaned.xlsx' for processed data where creative habits are assigned as tags.
Mapping of detailed discipline tags to one of three broader disciplines (Arts, Science, Business)
Mapping of free text gender entries to one of three genders: Male, Female, Non-Binary.
Survey responses where all creative habit ordinal responses were converted to Creative Habit Tags - these tags were used in the analysis to build a network of people linked if they share similar creative habit sets, or a network of creative habits linked if the co-occur in the similar sets of people.
This is a proprietary dataset from a large internet services company of ranked pairs of relevant and irrelevant businesses for different queries, for a total of 17,069 pairs. How well a query matches a candidate is represented by 41 features.
This public dataset contains 127,820 comments from Wikipedia Talk Pages labeled with whether or not they are toxic
Ensemble Tagger Training and Testing Set This data includes two files: The training set used to create the SCANL Ensemble tagger [1] and the "unseen" testing set that includes words from systems that are not available in the training set. These are derived from a prior dataset of Grammar Patterns; described in a different paper [2]. Within each of these csv files, you'll find several columns. We explain these columns below:
We aim to improve the bAbI benchmark as a means of developing intelligent dialogue agents. To this end, we propose concatenated-bAbI (catbAbI): an infinite sequence of bAbI stories. catbAbI is generated from the bAbI dataset and during training, a random sample/story from any task is drawn without replacement and concatenated to the ongoing story. The preprocessig for catbAbI addresses several issues: it removes the supporting facts, leaves the questions embedded in the story, inserts the correct answer after the question mark, and tokenises the full sample into a single sequence of words. As such, catbAbI is designed to be trained in an autoregressive way and analogous to closed-book question answering.