Mustaqeem

Orcid: 0000-0002-8020-3590

Affiliations:
  • Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI), Department of Computer Vision, Abu Dhabi, United Arab Emirates


According to our database1, Mustaqeem authored at least 26 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Online presence:

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Bibliography

2024
VD-Net: An Edge Vision-Based Surveillance System for Violence Detection.
IEEE Access, 2024

CamoFocus: Enhancing Camouflage Object Detection with Split-Feature Focal Modulation and Context Refinement.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

Action Knowledge Graph for Violence Detection Using Audiovisual Features.
Proceedings of the IEEE International Conference on Consumer Electronics, 2024

SpotCrack: Leveraging a Lightweight Framework for Crack Segmentation in Infrastructure.
Proceedings of the IEEE International Conference on Consumer Electronics, 2024

Skin-Former: Mobile-Friendly Transformer for Skin Lesion Diagnosis.
Proceedings of the IEEE International Conference on Consumer Electronics, 2024

2023
AAD-Net: Advanced end-to-end signal processing system for human emotion detection & recognition using attention-based deep echo state network.
Knowl. Based Syst., 2023

Deteriorated image classification model for malayalam palm leaf manuscripts.
J. Intell. Fuzzy Syst., 2023

TC-Net: A Modest & Lightweight Emotion Recognition System Using Temporal Convolution Network.
Comput. Syst. Sci. Eng., 2023

Improving Stain Invariance of CNNs for Segmentation by Fusing Channel Attention and Domain-Adversarial Training.
Proceedings of the Medical Imaging with Deep Learning, 2023

Metaverse Key Technologies and Blockchains: Impacts & Considerations.
Proceedings of the IEEE International Conference on Metaverse Computing, 2023

DDNet: Diabetic Retinopathy Detection System Using Skip Connection-based Upgraded Feature Block.
Proceedings of the IEEE International Symposium on Medical Measurements and Applications, 2023

ARTriViT: Automatic Face Recognition System Using ViT-Based Siamese Neural Networks with a Triplet Loss.
Proceedings of the 32nd IEEE International Symposium on Industrial Electronics, 2023

Gaming-Based Education System for Children on Road Safety in Metaverse Towards Smart Cities.
Proceedings of the IEEE International Smart Cities Conference, 2023

Combating Counterfeit Products in Smart Cities with Digital Twin Technology.
Proceedings of the IEEE International Smart Cities Conference, 2023

RECOD: Resource-Efficient Camouflaged Object Detection for UAV-Based Smart Cities Applications.
Proceedings of the IEEE International Smart Cities Conference, 2023

An Efficient Violence Detection Approach for Smart Cities Surveillance System.
Proceedings of the IEEE International Smart Cities Conference, 2023

PD-Net: Multi-Stream Hybrid Healthcare System for Parkinson's Disease Detection using Multi Learning Trick Approach.
Proceedings of the 36th IEEE International Symposium on Computer-Based Medical Systems, 2023

2021
Age and Gender Recognition Using a Convolutional Neural Network with a Specially Designed Multi-Attention Module through Speech Spectrograms.
Sensors, 2021

Optimal feature selection based speech emotion recognition using two-stream deep convolutional neural network.
Int. J. Intell. Syst., 2021

Human action recognition using attention based LSTM network with dilated CNN features.
Future Gener. Comput. Syst., 2021

MLT-DNet: Speech emotion recognition using 1D dilated CNN based on multi-learning trick approach.
Expert Syst. Appl., 2021

Att-Net: Enhanced emotion recognition system using lightweight self-attention module.
Appl. Soft Comput., 2021

Short-Term Energy Forecasting Framework Using an Ensemble Deep Learning Approach.
IEEE Access, 2021

2020
A CNN-Assisted Enhanced Audio Signal Processing for Speech Emotion Recognition.
Sensors, 2020

Deep-Net: A Lightweight CNN-Based Speech Emotion Recognition System Using Deep Frequency Features.
Sensors, 2020

Clustering-Based Speech Emotion Recognition by Incorporating Learned Features and Deep BiLSTM.
IEEE Access, 2020


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