Understanding deep learning techniques for recognition of human emotions using facial expressions: A comprehensive survey

M Karnati, A Seal, D Bhattacharjee… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Emotion recognition plays a significant role in cognitive psychology research. However,
measuring emotions is a challenging task. Thus, several approaches have been designed …

Poster++: A simpler and stronger facial expression recognition network

J Mao, R Xu, X Yin, Y Chang, B Nie, A Huang… - Pattern Recognition, 2024 - Elsevier
The POSTER has achieved SOTA performance in facial expression recognition (FER) by
effectively combining facial landmarks and image features through its two-stream pyramid …

Deception detection with machine learning: A systematic review and statistical analysis

AS Constâncio, DF Tsunoda, HFN Silva, JM Silveira… - Plos one, 2023 - journals.plos.org
Several studies applying Machine Learning to deception detection have been published in
the last decade. A rich and complex set of settings, approaches, theories, and results is now …

A dual-channel dehaze-net for single image dehazing in visual Internet of Things using PYNQ-Z2 board

G Sahu, A Seal, A Yazidi… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
A large number of emerging applications, such as autonomous navigation, space
exploration, surveillance, military target detection, and remote sensing, use outdoor images …

A novel multi-scale based deep convolutional neural network for detecting COVID-19 from X-rays

M Karnati, A Seal, G Sahu, A Yazidi, O Krejcar - Applied Soft Computing, 2022 - Elsevier
The COVID-19 pandemic has posed an unprecedented threat to the global public health
system, primarily infecting the airway epithelial cells in the respiratory tract. Chest X-ray …

Academic emotion classification using FER: A systematic review

JXY Lek, J Teo - Human Behavior and Emerging Technologies, 2023 - Wiley Online Library
Facial emotion expressions are among the most potent, natural, and powerful means of
human communication. Due to the COVID‐19 pandemic, educational institutions worldwide …

Benchmarks for machine learning in depression discrimination using electroencephalography signals

A Seal, R Bajpai, M Karnati, J Agnihotri, A Yazidi… - Applied …, 2023 - Springer
Diagnosis of depression using electroencephalography (EEG) is an emerging field of study.
When mental health facilities are unavailable, the use of EEG as an objective measure for …

Audio-visual deception detection: Dolos dataset and parameter-efficient crossmodal learning

X Guo, NM Selvaraj, Z Yu, AWK Kong… - Proceedings of the …, 2023 - openaccess.thecvf.com
Deception detection in conversations is a challenging yet important task, having pivotal
applications in many fields such as credibility assessment in business, multimedia anti …

Intelligent techniques for deception detection: a survey and critical study

H Alaskar, Z Sbaï, W Khan, A Hussain, A Alrawais - Soft Computing, 2023 - Springer
Abstract Machine intelligence methods originated as effective tools for generating learning
representations of features directly from the data and have indicated usefulness in the area …

A pyramidal spatial-based feature attention network for schizophrenia detection using electroencephalography signals

M Karnati, G Sahu, A Gupta, A Seal… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Automatic signal classification is utilized in various medical and industrial applications,
particularly in schizophrenia (SZ) diagnosis, one of the most prevalent chronic neurological …