19,997 machine learning datasets
19,997 dataset results
This file contains the data and code for the publication "The Federal Reserve's Response to the Global Financial Crisis and Its Long-Term Impact: An Interrupted Time-Series Natural Experimental Analysis" by A. C. Kamkoum, 2023.
Baidu PersonaChat, which is a personalization dataset collected and open-sourced by Baidu, is similar to ConvAI2, although it’s Chinese.
We introduce a large-scale video dataset Slovo for Russian Sign Language task. Slovo dataset size is about 16 GB, and it contains 20400 RGB videos for 1000 sign language gestures from 194 singers. Each class has 20 samples. The dataset is divided into training set and test set by subject user_id. The training set includes 15300 videos, and the test set includes 5100 videos. The total video recording time is ~9.2 hours. About 35% of the videos are recorded in HD format, and 65% of the videos are in FullHD resolution. The average video length with gesture is 50 frames.
A dataset of 100K synthetic images of skin lesions, ground-truth (GT) segmentations of lesions and healthy skin, GT segmentations of seven body parts (head, torso, hips, legs, feet, arms and hands), and GT binary masks of non-skin regions in the texture maps of 215 scans from the 3DBodyTex.v1 dataset [2], [3] created using the framework described in [1]. The dataset is primarily intended to enable the development of skin lesion analysis methods. Synthetic image creation consisted of two main steps. First, skin lesions from the Fitzpatrick 17k dataset were blended onto skin regions of high-resolution three-dimensional human scans from the 3DBodyTex dataset [2], [3]. Second, two-dimensional renders of the modified scans were generated.
InstructOpenWiki is a substantial instruction tuning dataset for Open-world IE enriched with a comprehensive corpus, extensive annotations, and diverse instructions.
a character sheet dataset containing over 700,000 hand-drawn and synthesized images of diverse poses
COCO-OOD dataset contains only unknown categories, consisting of 504 images with fine-grained annotations of 1655 unknown objects. All annotations consist of original annotations in COCO and the augmented annotations on the basis of the COCO definition.
COCO-Mixed dataset includes 897 images with annotations of both known and unknown categories. It contains 2533 unknown objects and 2658 known objects, with original COCO annotations used as labels for known objects. Unambiguous unlabeled objects are also annotated. The dataset is more challenging to evaluate due to the images containing more object instances with complex categories and concentrated locations.
UTCD is a compilation of 18 classification datasets spanning 3 categories of Sentiment, Intent/Dialogue, and Topic classification. UTCD focuses on the task of zero-shot text classification where the candidate labels are descriptive of the text being classified. UTCD consists of ~ 6M/800K train/test examples.
We consider the task of temporal human action localization in lifestyle vlogs. We introduce a novel dataset consisting of manual annotations of temporal localization for 13,000 narrated actions in 1,200 video clips. We present an extensive analysis of this data, which allows us to better understand how the language and visual modalities interact throughout the videos. We propose a simple yet effective method to localize the narrated actions based on their expected duration. Through several experiments and analyses, we show that our method brings complementary information with respect to previous methods and leads to improvements over previous work for the task of temporal action localization.
This dataset provides neutron and gamma-ray pulse signals for pulse shape discrimination experiments. Serval traditional and recently proposed pulse shape discrimination algorithms are utilized to conduct pulse shape discrimination under raw pulse signals and noise-enhanced datasets. These algorithms include zero-crossing (ZC), charge comparison (CC), falling edge percentage slope (FEPS), frequency gradient analysis (FGA), pulse-coupled neural network (PCNN), ladder gradient (LG), and heterogeneous quasi-continuous spiking cortical model (HQC-SCM). This dataset also provides the source code of all these pulse shape discrimination methods, together with the source code of schematic pulse shape discrimination performance evaluation and anti-noise performance evaluation.
NaSGEC is a new dataset to facilitate research on Chinese grammatical error correction (CGEC) for native speaker texts from multiple domains. Previous CGEC research primarily focuses on correcting texts from a single domain, especially learner essays.
CN-Celeb-AV is a multi-genre AVPR dataset collected 'in the wild'. This dataset contains more than 420k video segments from 1,136 persons from public media.
MADDPG AND P2P-VFRL FOR MINIMIZING AOI IN NTN NETWORK UNDER CSI UNCERTAINTY
3D confocal stacks with corresponding 2D Light-field microscope images
Dataset Summary New dataset introduced in Parameter-Efficient Legal Domain Adaptation (Li et al., 2022) from the Legal Advice Reddit community (known as "/r/legaldvice"), sourcing the Reddit posts from the Pushshift Reddit dataset. The dataset maps the text and title of each legal question posted into one of eleven classes, based on the original Reddit post's "flair" (i.e., tag). Questions are typically informal and use non-legal-specific language. Per the Legal Advice Reddit rules, posts must be about actual personal circumstances or situations. We limit the number of labels to the top eleven classes and remove the other samples from the dataset.
Curated QA Benchmark on State of the Union Address 2023. It contains curated question and answers based on knowledge presented in State of the Union Address 2023 (in Feb). It is especially useful for tool-augmented LMs / ALMs to examine the model's ability in answering over private document.
WMVeID863 is captured with vehicles in motion with more challenges, such as motion blur, huge background changes, and especially intense flare degradation from car lamps, and sunlight. It contains 863 identities of vehicle triplets (RGB, NI, and TI) captured with 8 camera views at a traffic checkpoint, contributing 14127 images.
This dataset contains annual Sentinel-2 MSI composites (wet and dry season) for Kigali for the period 2016-2020. In addition, a metadata file containing population count at the grid level (100 x 100 m) for 2020 and at the census level (administrative units) for 2016 and 2020 is provided. Ancillary data such as the administrative boundaries of Kigali are also available.
Sonicverse is a multisensory simulation platform with integrated audio-visual simulation for training household agents that can both see and hear. Sonicverse models realistic continuous audio rendering in 3D environments in real-time. Together with a new audio-Visual VR interface that allows humans to interact with agents with audio, Sonicverse enables a series of embodied AI tasks that need audio-visual perception.