Omkar2118/datasets huggingface dataset:
ISBNet

ISBNet is a dataset of images of recyclables. It is hand collected by our group at the International School of Beijing. The trash in these images was gathered from trash bins around the school. ISBNet totals 889 images distributed across 5 classes: cans (74), landfill (410), paper (182), plastic (122), and tetra pak (101). The data acquisition process involved using a piece of black poster paper as a background; this would create enough contrast for trash belonging to the paper category. These pictures were taken with an iPhone 8 and an iPhone XS. We recorded the trash bin in which the piece of trash originated from and any trash generating landmarks nearby.  Please refer to the paper (ThanosNet: A Novel Trash Classification Method Using Metadata) for more about the format of the metadata.

Introducing paper: ThanosNet: A Novel Trash Classification Method Using Metadata
TUH EEG Seizure Corpus
Full name: Temple University Hospital (TUH) EEG Corpus

Our goal is to enable deep learning research in neuroscience by releasing the largest publicly available unencumbered database of EEG recordings. This ongoing project currently includes over 30,000 EEGs spanning the years from 2002 to present. Data collected can be used for both research and commercialization purposes.

Iyad Obeid and Joseph Picone. The temple university hospital eeg data corpus. Frontiers in neuroscience,10:196, 2016.
PPG  Dalia
Full name: PPG Field Study Dataset

PPG-DaLiA is a publicly available dataset for PPG-based heart rate estimation. This multimodal dataset features physiological and motion data, recorded from both a wrist- and a chest-worn device, of 15 subjects while performing a wide range of activities under close to real-life conditions. The included ECG data provides heart rate ground truth. The included PPG- and 3D-accelerometer data can be used for heart rate estimation, while compensating for motion artefacts.