In My study, we evaluate the performance of the proposed clustering method across a wide range of publicly available datasets that represent different data modalities. Specifically, Jaffe, ExtendYaleB, and ORL are employed as facial image datasets to assess the method's capability in handling variations in facial expressions and lighting conditions.
This dataset is designed for research on 2D Multi-frequency Electrical Impedance Tomography (mfEIT). It includes:
El dataset desarrollado integra múltiples dimensiones relevantes para el análisis académico y profesional de los estudiantes.
The ABERDEEN Face Database is a well-known dataset in the field of computer vision and pattern recognition, specifically designed for research into face detection, recognition, and related tasks. Compiled by researchers at the University of Aberdeen in Scotland, this database provides a valuable resource for scientists and engineers working on facial analysis algorithms.
Please cite the following paper when using this dataset:
Vanessa Su and Nirmalya Thakur, “COVID-19 on YouTube: A Data-Driven Analysis of Sentiment, Toxicity, and Content Recommendations”, Proceedings of the IEEE 15th Annual Computing and Communication Workshop and Conference 2025, Las Vegas, USA, Jan 06-08, 2025 (Paper accepted for publication, Preprint: https://arxiv.org/abs/2412.17180).
Abstract:
To download this dataset without purchasing an IEEE Dataport subscription, please visit: https://zenodo.org/records/13896353
Please cite the following paper when using this dataset:
To download the dataset without purchasing an IEEE Dataport subscription, please visit: https://zenodo.org/records/13738598
Please cite the following paper when using this dataset:
N. Thakur, “Mpox narrative on Instagram: A labeled multilingual dataset of Instagram posts on mpox for sentiment, hate speech, and anxiety analysis,” arXiv [cs.LG], 2024, URL: https://arxiv.org/abs/2409.05292
Abstract
This dataset contains simulation values from thermo-mechanical finite element analysis simulations using ABAQUS. Each simulation is one of 192 unique process parameter settings which includes varying laser power, scan speed, layer height and cooling assumptions. The geometry for each simulation is a hollow rectangluar box with rounded corners such that they form semi-circles. The wall thickness of each simulation is exactly the width of the focused laser.
A commonly used definition of spatial disorientation (SD) in aviation is "an erroneous sense of one’s position and motion relative to the plane of the earth’s surface". There exists a wide range of SD use-cases dictated by situational factors, therefore SD has been predominantly studied using reduced motion detection experimental contexts in isolation. The study of SD by use-case makes it difficult to understand general SD occurrence and thus provide viable solutions. To investigate SD in a generalized manner, a two-part Human Activity Recognition (HAR) study was performed.
