Omkar2118/datasets huggingface dataset:
PubChem: Antagonist of Human D 1 Dopamine Receptor: qHTS
Full name: PubChem: Antagonist of Human D 1 Dopamine Receptor: qHTS

he goal of this project is to use high throughput screening approaches to identify and develop novel, highly selective small molecule allosteric modulators of the D1 DAR for use as in vitro and in vivo pharmacological tools and in proof-of-concept experiments in animal models of neuropsychiatric disease. There are three different types of allosteric modulators that we are seeking, two of which will stimulate or augment receptor signaling, allosteric agonists and potentiators, while the third, allosteric antagonists, will attenuate receptor signaling. The present primary screening assay measures compound antagonism after an EC80 addition of dopamine by tracking calcium flux in a force-coupled, inducible Hek293 Trex D1 cell line.
Data for: Neuromorphic weighted sums with magnetic skyrmions

The following experimental data were obtained on lithography devices made of magnetic multilayer tracks and thin tantalum transverse electrodes by Kerr microscopy and anomalous Hall effect measurements. The results, demonstrating the weighted sum operation using magnetic skyrmions, are published in T. da Câmara Santa Clara Gomes et al., Neuromorphic weighted sums with magnetic skyrmions, Nature Electronics (2024). Please find in the README additional information regarding the data files and the variables.

Introducing paper: Neuromorphic weighted sum with magnetic skyrmions
Multi-behavior Taobao

Data from the popular Chinese online shopping platform Taobao includes behaviors like buy, add-to-cart, add-to-favorite, and pageview. The buying behavior is considered the target behavior.
WayveScenes101

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Introducing paper: WayveScenes101: A Dataset and Benchmark for Novel View Synthesis in Autonomous Driving
CoNLL-2020
Full name: CoNLLpp

A test dataset that annotated articles in 2020 following the CoNLL-2003 NER task.

Introducing paper: Do CoNLL-2003 Named Entity Taggers Still Work Well in 2023?
University

Univesity is an indoor localization dataset proposed in "Camera Relocalization by Computing Pairwise Relative Poses Using Convolutional Neural Network". 

It contains camera images and ground-truth poses, split in 9694 training pairs and 5068 test pairs.

It was created to test localization of multiple scenes in one global coordinate frame, and has a bigger indoor environment compared to 7scenes.

Introducing paper: Camera Relocalization by Computing Pairwise Relative Poses Using Convolutional Neural Network
Drone-Anomaly
Full name: Drone-Anomaly

Drone-Anomaly rovides 37 training video sequences and 22 testing video sequences from 7 different realistic scenes with various anomalous events. There are 87,488 color video frames (51,635 for training and 35,853 for testing) with the size of 640 × 640 at 30 frames per second.