Artificial Intelligence

The problem of effective disposal of the trash generated by people has rightfully attracted major interest from various sections of society in recent times. Recently, deep learning solutions have been proposed to design automated mechanisms to segregate waste. However, most datasets used for this purpose are not adequate. In this paper, we introduce a new dataset, TrashBox, containing 17,785 images across seven different classes, including medical and e-waste classes which are not included in any other existing dataset.

Guava fruit production is one of the main sources of economic growth in Asian countries, the world production of guava in 2019 was 55 million tons. Guava disease is an important factor in economic loss as well as quantity and quality of guava. The original guava fruit disease dataset consist of 38 images of phytophthora, 30 images of root and 34 images of scab guava disease with 650x650x3 pixel.

This is a manually curated corpus for the LOD dataset classification task. The corpus includes datasets from three sources: (i) ontologies indexed by LOV, (ii) datasets crawled by LOD Laundromat, (iii) the Topic

A synthetic laser reliability dataset generated using generative  adversarial networks (GANs) is provided. The data includes normalized current measurements estimated at the following times: 2, 20, 40, 60, 80, 100, 150, 500, 1000, and 1500 hours. The data can be used to train machine learning models to solve different predictive maintenance tasks such as prediction of performance degradation, remainng useful prediction, and so on. 

This dataset is a face dataset collected for the purpose of a face anti-spoofing study.

The dataset contains labeled sentences. The sentences having information related to (1) infections, (2) suffering from pneumonea, (3) deaths, and (4) health updates from government/WHO, are labeled with 1 and the rest are labeled with 0. Source of all the news articles: https://www.thehindu.com/archive/

Building segmentation image data set

This dataset is for doa estimation when an amplitude-phase error exists.

These datasets contain the database of the local television channels in the greater manila 
area (GMA) in the Philippines as of 2020.

Touch-screens are the basic and convenient human-computer interface. They are extensively used in digital musical applications, where a complex action-perception loop is involved. Therefore, it is crucial to establish a rich vibrotacticle feedback to improve the quality of the user's interaction. This paper explores the capacity of Generative Adversarial Networks (GANs) to generate time-reversed signals that can achieve localized vibrotactile feedback on a rigid surface.