Omkar2118/datasets huggingface dataset:
CreditRisk
Full name: TransUnion TransRisks Scores

Dataset containing Credit scores and loan repayment rate (90-day default rate) for individuals, separated by race (white, black, Hispanic Asian).

Introducing paper: Equality of Opportunity in Supervised Learning
COMPAS
Full name: machine bias risk assessments in criminal sentencing

Dataset used by ProPublica to assess and analyse the fairness of the COMPAS (Correctional Offender Management Profiling for Alternative Sanctions) software.

compas.db - a sqlite3 database containing criminal history, jail and prison time, demographics and COMPAS risk scores for defendants from Broward County.
COVIDx CXR-3

COVIDx CXR-3 is an open access benchmark dataset that we generated, comprising 30,882 CXR images across 17,026 patient cases. Images may be added over time to improve the dataset.

This dataset is being used to train and validate our models for COVID-19 detection from CXR images. Useful dataset code and manipulation tools are available in the COVID-Net repository. This dataset may also be constructed from the individual sources by following the instructions here.
pinkeggs

We introduce a novel dataset consisting of images depicting pink eggs that have been identified as Pomacea canaliculata eggs, accompanied by corresponding bounding box annotations. The purpose of this dataset is to aid researchers in the analysis of the spread of Pomacea canaliculata species by utilizing deep learning techniques, as well as supporting other investigative pursuits that require visual data pertaining to the eggs of Pomacea canaliculata. It is worth noting, however, that the identity of the eggs in question is not definitively established, as other species within the same taxonomic family have been observed to lay similar-looking eggs in regions of the Americas. Therefore,
a crucial prerequisite to any decision regarding the elimination of these eggs would be to establish with certainty whether they are exclusively attributable to invasive Pomacea canaliculata or if other species are also involved. The dataset is available at
https://www.kaggle.com/datasets/deeshenzhen/pinkeggs

Introducing paper: Pink-Eggs Dataset V1: A Step Toward Invasive Species Management Using Deep Learning Embedded Solutions
DOTA 2.0
Full name: Dataset of Object deTection in Aerial images

—In the past decade, object detection has achieved significant progress in natural images but not in aerial images, due to the
massive variations in the scale and orientation of objects caused by the bird’s-eye view of aerial images. More importantly, the lack of
large-scale benchmarks has become a major obstacle to the development of object detection in aerial images (ODAI). In this paper,
we present a large-scale Dataset of Object deTection in Aerial images (DOTA) and comprehensive baselines for ODAI. The proposed
DOTA dataset contains 1,793,658 object instances of 18 categories of oriented-bounding-box annotations collected from 11,268 aerial
images. Based on this large-scale and well-annotated dataset, we build baselines covering 10 state-of-the-art algorithms with over 70
configurations, where the speed and accuracy performances of each model have been evaluated. Furthermore, we provide a code
library for ODAI and build a website for evaluating different algorithms. Previous challenges run on DOTA have attracted more than 1300
teams worldwide. We believe that the expanded large-scale DOTA dataset, the extensive baselines, the code library and the challenges
can facilitate the designs of robust algorithms and reproducible research on the problem of object detection in aerial images.

Introducing paper: Object Detection in Aerial Images: A Large-Scale Benchmark and Challenges