Omkar2118/datasets huggingface dataset:
Sydney Urban Objects

This dataset contains a variety of common urban road objects scanned with a Velodyne HDL-64E LIDAR, collected in the CBD of Sydney, Australia. There are 631 individual scans of objects across classes of vehicles, pedestrians, signs and trees.

It was collected in order to test matching and classification algorithms. It aims to provide non-ideal sensing conditions that are representative of practical urban sensing systems, with a large variability in viewpoint and occlusion.

Source: [http://www.acfr.usyd.edu.au/papers/SydneyUrbanObjectsDataset.shtml](http://www.acfr.usyd.edu.au/papers/SydneyUrbanObjectsDataset.shtml)
Image Source: [http://www.acfr.usyd.edu.au/papers/SydneyUrbanObjectsDataset.shtml](http://www.acfr.usyd.edu.au/papers/SydneyUrbanObjectsDataset.shtml)
Brazil Air-Traffic
Full name: Brazil Air-Traffic

Brazil Air-Traffic

Introducing paper: struc2vec: Learning Node Representations from Structural Identity
USA Air-Traffic
Full name: USA Air-Traffic

Leonardo Filipe Rodrigues Ribeiro, Pedro H. P. Saverese, and Daniel R. Figueiredo. struc2vec: Learning node
representations from structural identity.

Introducing paper: struc2vec: Learning Node Representations from Structural Identity
Mutagenicity

**Mutagenicity** is a chemical compound dataset of drugs, which can be categorized into two classes: mutagen and non-mutagen.

Source: [Hierarchical Graph Pooling with Structure Learning](https://arxiv.org/abs/1911.05954)
SIDER
Full name: SIDER

**SIDER** contains information on marketed medicines and their recorded adverse drug reactions. The information is extracted from public documents and package inserts. The available information include side effect frequency, drug and side effect classifications as well as links to further information, for example drug–target relations.

Source: [Side Effect Resource](http://sideeffects.embl.de/)
Image Source: [http://sideeffects.embl.de/drugs/2756/](http://sideeffects.embl.de/drugs/2756/)
clintox

The ClinTox dataset compares drugs approved by the FDA and drugs that have failed clinical trials for toxicity reasons. The dataset includes two classification tasks for 1491 drug compounds with known chemical structures: (1) clinical trial toxicity (or absence of toxicity) and (2) FDA approval status.