Omkar2118/datasets huggingface dataset:
SEN
Full name: Sentiment analysis of Entities in News headlines

SEN is a novel publicly available human-labelled dataset for training and testing machine learning algorithms for the problem of entity level sentiment analysis of political news headlines.

Dataset consists of 3819 human-labelled political news headlines coming from several major on-line media outlets in English and Polish.
SeaDronesSee
Full name: SeaDronesSee: A Maritime Benchmark for Detecting Humans in Open Water

SeaDronesSee is a large-scale data set aimed at helping develop systems for Search and Rescue (SAR) using Unmanned Aerial Vehicles (UAVs) in maritime scenarios. Building highly complex autonomous UAV systems that aid in SAR missions requires robust computer vision algorithms to detect and track objects or persons of interest. This data set provides three sets of tracks: object detection, single-object tracking and multi-object tracking. Each track consists of its own data set and leaderboard.

Object Detection: 5,630 train images, 859 validation images, 1,796 testing images

Single-Object Tracking: 58 training video clips, 70 validation video clips and 80 testing video clips

Multi-Object Tracking: 22 video clips with 54,105 frames
Additionally, we provide multi-spektral footage:

Multi-Spektral Object Detection: 246 train images, 61 validation images, 125 testing images

We will continue to update this data set to make it more versatile and reflect real-world requirements in dynamic situations.

Introducing paper: SeaDronesSee: A Maritime Benchmark for Detecting Humans in Open Water
DGTA-VisDrone
Full name: DeepGTAV-VisDrone

Object Detection data set created from the engine DeepGTAV, which is based on the video game GTAV. Part of the three data sets proposed in the paper. This data set is motivated from the VisDrone data set with almost the same classes.

Introducing paper: Leveraging Synthetic Data in Object Detection on Unmanned Aerial Vehicles
DGTA-SeaDronesSee
Full name: DeepGTAV-SeaDronesSee

Object Detection data set created from the engine DeepGTAV, which is based on the video game GTAV. Part of the three data sets proposed in the paper. This data set is motivated from the SeaDronesSee dataset with almost the same classes.

Introducing paper: Leveraging Synthetic Data in Object Detection on Unmanned Aerial Vehicles
DGTA-Cattle
Full name: DeepGTAV-Cattle

Object Detection data set created from the engine DeepGTAV, which is based on the video game GTAV. Part of the three data sets proposed in the paper. This data set is motivated from the Cattle dataset with almost the same classes.

Introducing paper: Leveraging Synthetic Data in Object Detection on Unmanned Aerial Vehicles
Cattle

Cattle data set, which was introduced in a paper. We (not the authors) created a train-val-test split.