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imen JDEY

Associate Professor

Institute of Environmental Engineering

United States

Research Interests

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About

Imen JDEY is an Assistant Professor at the Institute of Electrical and Electronics Engineers in the United States. Their research focuses on privacy-aware technologies, deep learning applications in healthcare, and machine learning methodologies for disease detection. Recent publications include studies on malaria detection using advanced neural network models and the integration of blockchain in healthcare data privacy.

Articles (24)

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2022

Collaborators (1)

Awais Mahmood

Associate Prof

king saud university

SAUDI ARABIA

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imen JDEY

Research Interests

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About

Articles (24)

FuzzyVGG: Improving Uncertainty and Interpretability in Satellite Image Classification through Fuzzy Logic Integration

Synergizing CNNs and ViTs

A Native Supervision Approach to Arabic VLM: Overcoming Transliteration Bias for Semantic Accuracy

An Uncertainty-Aware Attention-Based Residual U-Net for Cochineal Insect Segmentation

An explainable deep learning model for dental caries detection and segmentation

BEFT vs. LoRA: Parameter-Efficient Fine-Tuning for Auto-OptimizeVision Transformers in Image Classification

Dynamic Weighted Multimodal Fusion for Explainable Chest X-Ray Segmentation Using Integrated Gradients

Explainable ResNet–Transformer Fusion with Belief Function Theory for Automated Infection Detection and Severity Assessment in Cactus Pears

Residual U-Net with Spatial Feature Refinement and Channel Sensitivity Enhancement for Accurate Segmentation of Cochineal Insect Infestation

Towards Privacy-Aware and Explainable Alzheimer's Diagnosis Using Lime and Federated Learning

Auto-Optimized Parameter-Efficient Fine-Tuning for Skin Lesion Classification with Vision Transformers

Automated Impacted Tooth Segmentation in Panoramic Radiographs Using UNet and UNet3+ with Grad-CAM Explainability

Boosting Hyperspectral Image Classification with a 3D CNN and Vision Transformer Hybrid Architecture

Federated Learning Harnessed with Differential Privacy for Heart Disease Prediction: Enhancing Privacy and Accuracy

IoT-Enhanced Tomato Leaf Disease Identification Using MLP-Mixer in Agricultural Environments

K-Means Clustered Quantization for Efficient CNN-Based Skin Lesion Classification

Towards Explainable Skin Cancer Diagnosis: A Vision Transformer Approach with Grad-CAM Visualization

PRIVACY-AWARE MALARIA DETECTION: U-NET MODEL WITH K-ANONYMITY FOR CONFIDENTIAL IMAGE ANALYSIS

Deep Learning and Machine Learning for Malaria Detection: Overview, Challenges and Future Directions

Automatic tooth instance segmentation and identification from panoramic X-Ray images using deep CNN

A blockchain-based federated learning mechanism for privacy preservation of healthcare IoT data

Deep Learning and Machine Learning for Malaria Detection: Overview, Challenges and Future Directions

Study of Different Deep Learning Methods for Coronavirus (COVID-19) Pandemic: Taxonomy, Survey and Insights

Improving Malaria Detection Using L1 Regularization Neural Network

Collaborators (1)

Awais Mahmood

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