Syed Mohsen Naqvi
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View article: Robust super-twisting algorithm-based single-phase sliding mode frequency controller in power systems integrating wind turbines and energy storage systems
Robust super-twisting algorithm-based single-phase sliding mode frequency controller in power systems integrating wind turbines and energy storage systems Open
View article: Thermal gradient effects on steel I-girders in bridges: A review
Thermal gradient effects on steel I-girders in bridges: A review Open
Steel I-girders in bridges experience thermal gradients induced by environmental factors, which generate non-uniform stresses, resulting in deformation, fatigue, and dynamic impacts, causing reduced service life. This review consolidates t…
View article: Efficient Long Speech Sequence Modelling for Time-Domain Depression Level Estimation
Efficient Long Speech Sequence Modelling for Time-Domain Depression Level Estimation Open
Depression significantly affects emotions, thoughts, and daily activities. Recent research indicates that speech signals contain vital cues about depression, sparking interest in audio-based deep-learning methods for estimating its severit…
View article: A Novel Audio-Visual Information Fusion System for Mental Disorders Detection
A Novel Audio-Visual Information Fusion System for Mental Disorders Detection Open
Mental disorders are among the foremost contributors to the global healthcare challenge. Research indicates that timely diagnosis and intervention are vital in treating various mental disorders. However, the early somatization symptoms of …
View article: ADHD detection based on human action recognition
ADHD detection based on human action recognition Open
Attention Deficit Hyperactivity Disorder (ADHD) is a highly prevalent human neurobehavioral and neurodevelopmental disorder worldwide. Recently, deep learning-based techniques have been exploited in ADHD detection and diagnosis due to thei…
View article: Acoustic and Text Features Analysis for Adult ADHD Screening: A Data-Driven Approach Utilizing DIVA Interview
Acoustic and Text Features Analysis for Adult ADHD Screening: A Data-Driven Approach Utilizing DIVA Interview Open
Attention Deficit Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder commonly seen in childhood that leads to behavioural changes in social development and communication patterns, often continues into undiagnosed adulthood due …
View article: Insights Into Detecting Adult ADHD Symptoms Through Advanced Dual-Stream Machine Learning
Insights Into Detecting Adult ADHD Symptoms Through Advanced Dual-Stream Machine Learning Open
Advancements in machine learning offer promising avenues for the identification of ADHD symptoms in adults, an endeavour traditionally encumbered by the intricacies of human behavioural patterns. In this paper, we introduce three innovativ…
View article: Pose-Oriented Scene-Adaptive Matching for Abnormal Event Detection
Pose-Oriented Scene-Adaptive Matching for Abnormal Event Detection Open
View article: 24 Intelligent sensing in ADHD trial (ISAT) – pilot study
24 Intelligent sensing in ADHD trial (ISAT) – pilot study Open
Objectives/Aims To the best of our knowledge, there are no studies using intelligent sensing to diagnose ADHD. The aim of this interdisciplinary (Medical and Engineering) research is to contribute intelligent sensing based multimodal (audi…
View article: Learning with Noisy Labels for Human Fall Events Classification: Joint Cooperative Training with Trinity Networks
Learning with Noisy Labels for Human Fall Events Classification: Joint Cooperative Training with Trinity Networks Open
With the increasing ageing population, fall events classification has drawn much research attention. In the development of deep learning, the quality of data labels is crucial. Most of the datasets are labelled automatically or semi-automa…
View article: Position and Orientation-Aware One-Shot Learning for Medical Action Recognition from Signal Data
Position and Orientation-Aware One-Shot Learning for Medical Action Recognition from Signal Data Open
In this work, we propose a position and orientation-aware one-shot learning framework for medical action recognition from signal data. The proposed framework comprises two stages and each stage includes signal-level image generation (SIG),…
View article: Programme
Programme Open
View article: Image Formation Algorithms for Low-Cost Freehand Ultrasound Scanner Based on Ego-Motion Estimation and Unsupervised Clustering
Image Formation Algorithms for Low-Cost Freehand Ultrasound Scanner Based on Ego-Motion Estimation and Unsupervised Clustering Open
This paper describes the application of unsupervised learning techniques to improve ego-motion estimation for a low-cost freehand ultrasound probe. Echo decorrelation measurements, which are used to estimate the lateral velocity of a scann…
View article: Abnormal event detection for video surveillance using an enhanced two-stream fusion method
Abnormal event detection for video surveillance using an enhanced two-stream fusion method Open
Abnormal event detection is a critical component of intelligent surveillance systems, focusing on identifying abnormal objects or unusual human behaviours in video sequences. However, conventional methods struggle due to the scarcity of la…
View article: Skeleton-based action analysis for ADHD diagnosis
Skeleton-based action analysis for ADHD diagnosis Open
Attention Deficit Hyperactivity Disorder (ADHD) is a common neurobehavioral disorder worldwide. While extensive research has focused on machine learning methods for ADHD diagnosis, most research relies on high-cost equipment, e.g., MRI mac…
View article: Phase-Aware Complex-Cycle-Consistent Self-Supervised Learning for Monaural Speech Enhancement
Phase-Aware Complex-Cycle-Consistent Self-Supervised Learning for Monaural Speech Enhancement Open
View article: Machine Learning in ADHD and Depression Mental Health Diagnosis: A Survey
Machine Learning in ADHD and Depression Mental Health Diagnosis: A Survey Open
This paper explores the current machine learning based methods used to identify Attention Deficit Hyperactivity Disorder (ADHD) and depression in humans. Prevalence of mental ADHD and depression is increasing worldwide, partly due to the d…
View article: ADHD diagnosis based on action characteristics recorded in videos using machine learning
ADHD diagnosis based on action characteristics recorded in videos using machine learning Open
View article: Abnormal Event Detection for Video Surveillance Using an Enhanced Two-Stream Fusion Method
Abnormal Event Detection for Video Surveillance Using an Enhanced Two-Stream Fusion Method Open
View article: Action-Based ADHD Diagnosis in Video
Action-Based ADHD Diagnosis in Video Open
Attention Deficit Hyperactivity Disorder (ADHD) causes significant impairment in various domains. Early diagnosis of ADHD and treatment could significantly improve the quality of life and functioning. Recently, machine learning methods hav…
View article: Pose‐driven human activity anomaly detection in a CCTV‐like environment
Pose‐driven human activity anomaly detection in a CCTV‐like environment Open
Human activity anomaly detection plays a crucial role in the next generation of surveillance and assisted living systems. Most anomaly detection algorithms are generative models and learn features from raw images. This work shows that popu…
View article: Two-stage Fall Events Classification with Human Skeleton Data
Two-stage Fall Events Classification with Human Skeleton Data Open
Fall detection and classification become an imper- ative problem for healthcare applications particularity with the increasingly ageing population. Currently, most of the fall clas- sification algorithms provide binary fall or no-fall clas…
View article: Feature Learning and Ensemble Pre-Tasks Based Self-Supervised Speech Denoising and Dereverberation
Feature Learning and Ensemble Pre-Tasks Based Self-Supervised Speech Denoising and Dereverberation Open
Self-supervised learning (SSL) achieves great success in monaural speech enhancement, while the accuracy of the target speech estimation, particularly for unseen speakers, remains inadequate with existing pre-tasks. As speech signal contai…
View article: Self-Supervised Learning based Monaural Speech Enhancement with Complex-Cycle-Consistent
Self-Supervised Learning based Monaural Speech Enhancement with Complex-Cycle-Consistent Open
Recently, self-supervised learning (SSL) techniques have been introduced to solve the monaural speech enhancement problem. Due to the lack of using clean phase information, the enhancement performance is limited in most SSL methods. Theref…
View article: Self-Supervised Learning based Monaural Speech Enhancement with Multi-Task Pre-Training
Self-Supervised Learning based Monaural Speech Enhancement with Multi-Task Pre-Training Open
In self-supervised learning, it is challenging to reduce the gap between the enhancement performance on the estimated and target speech signals with existed pre-tasks. In this paper, we propose a multi-task pre-training method to improve t…
View article: U-shaped Transformer with Frequency-Band Aware Attention for Speech Enhancement
U-shaped Transformer with Frequency-Band Aware Attention for Speech Enhancement Open
The state-of-the-art speech enhancement has limited performance in speech estimation accuracy. Recently, in deep learning, the Transformer shows the potential to exploit the long-range dependency in speech by self-attention. Therefore, it …
View article: Domain Adaptation and Autoencoder-Based Unsupervised Speech Enhancement
Domain Adaptation and Autoencoder-Based Unsupervised Speech Enhancement Open
As a category of transfer learning, domain adaptation plays an important role\nin generalizing the model trained in one task and applying it to other similar\ntasks or settings. In speech enhancement, a well-trained acoustic model can be\n…
View article: Convolutional fusion network for monaural speech enhancement
Convolutional fusion network for monaural speech enhancement Open
Convolutional neural network (CNN) based methods, such as the convolutional encoder-decoder network, offer state-of-the-art results in monaural speech enhancement. In the conventional encoder-decoder network, large kernel size is often use…
View article: Single‐channel dereverberation and denoising based on lower band trained SA‐LSTMs
Single‐channel dereverberation and denoising based on lower band trained SA‐LSTMs Open
The supervised single‐channel speech enhancement presents one mixture recording at the input of the neural network and updates network parameters in order to generate an output as the reconstructed speech signal. However, current neural ne…
View article: 2D Pose-Based Real-Time Human Action Recognition With Occlusion-Handling
2D Pose-Based Real-Time Human Action Recognition With Occlusion-Handling Open
Human Action Recognition (HAR) for CCTV-oriented applications is still a challenging problem. Real-world scenarios HAR implementations is difficult because of the gap between Deep Learning data requirements and what the CCTV-based framewor…