Artificial Intelligence

Dataset for Generative Adversarial Learning of Protein Tertiary Structures. Molecules, 2021.

Protein molecules are inherently dynamic and modulate their interactions with different molecular partners by accessing different tertiary structures under physiological conditions.Elucidating such structures remains challenging. Current momentum in deep learning and the powerful performance of generative adversarial networks (GANs) in complex domains, such as computer vision, inspires us to investigate GANs on their ability to generate physically-realistic protein tertiary structures.

Categories:: Artificial Intelligence
Machine Learning
Biomedical and Health Sciences

660 Views

LCANet: Lightweight Context-aware Attention Networks for Earthquake Detection and Phase Picking on IoT Edge Devices

This data set is the result of model test trained on the basis of the Stanford earthquake dataset (stead): a global data set of seismic signals for AI, which can effectively get the seismic signal and the arrival time of seismic phase from the image, so as to prove the effectiveness of this model

Categories:: Artificial Intelligence
IoT
Machine Learning
Digital signal processing

555 Views

Supplementary Files - Towards Development of an ISFET-based Smart pH Sensor: Enabling Machine Learning for Drift Compensation in IoT Applications

The dataset consists of the ISFET sensor data utilized to train ML models for drift compensation.

Categories:: Artificial Intelligence
Machine Learning
Computational Intelligence
Sensors

448 Views

A Multi-Agent Approach for Personalized Hypertension Risk Prediction

Categories:: Artificial Intelligence

436 Views

Trajectory Generation for Robotic Pick-and-Place Task Based on Nested Double-Memory Deep Deterministic Policy Gradient

Trajectory generation for robotic pick-and-place task using nested double-memory deep deterministic policy gradient.

Categories:: Artificial Intelligence

110 Views

Yonsei Stress Image Database

YonseiStressImageDatabase is a database built for image-based stress recognition research. We designed an experimental scenario consisting of steps that cause or do not cause stress; Native Language Script Reading, Native Language Interview, Non-native Language Script Reading, Non-native Language Interview. And during the experiment, the subjects were photographed with Kinect v2. We cannot disclose the original image due to privacy issues, so we release feature maps obtained by passing through the network.

Categories:: Artificial Intelligence
Signal Processing
Machine Learning
Image Processing
Computational Intelligence
Computer Vision

3068 Views

Data Set used in the conference paper titled "Short-Term Load Forecasting Using an LSTM Neural Network"

The data-set used in the paper titled "Short-Term Load Forecasting Using an LSTM Neural Network."

Categories:: Artificial Intelligence
Machine Learning
Power and Energy
Smart Grid

1544 Views

Cycle-consistent Generative Adversarial Networks for Neural Style Transfer using data from CE-4

Given the difficulty to handle planetary data we provide downloadable files in PNG format from the missions Chang'E-3 and Chang'E-4. In addition to a set of scripts to do the conversion given a different PDS4 Dataset.