Machine Learning

The credit risk evaluation data generated by a commercial bank’s personal consumption loans.

This dataset contains actual field/experimental data for the following environmental engineering applications, namely:

• Concentration data generated from filtration systems which treat influents, having contaminant materials, via adsorption process.
• Streamflow height data collated for 50 states/cities in America for the historical period between 1900-2018.

Opportunity++ is a precisely annotated dataset designed to support AI and machine learning research focused on the multimodal perception and learning of human activities (e.g. short actions, gestures, modes of locomotion, higher-level behavior).

CodeTiburon is a software development company and IT outsourcing provider, headquartered in Kharkiv and delivering high-end solutions to precise specifications since 2009.

Computer vision and image processing have made significant progress in many real-world applications, including environmental monitoring and protection. Recent studies have shown that computer vision and image processing can be used to quantify water turbidity, a crucial physical parameter in water quality assessment. This paper presents a procedure to determine water turbidity using deep learning methods, specifically, convolutional neural network (CNN). At first, water samples were located inside a dark cabin before digital images of the samples were captured with a smartphone camera.

a novel two-electrode, frequency-scan electrical impedance tomography (EIT) system for gesture recognition

The dataset consists of samples of DDoS attacks. The samples were generated either by dedicated tools such as Loic, Hulk, Thorshammer, or combined from publicly available source such as from DDoS Evaluation Dataset (CIC-DDoS2019).