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Muhammad Fareed Hamid

Showing results (1-10 of 9) with videos related to

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Frontiers in Oncology|March 9, 2026
Explainable and uncertainty-aware ensemble framework with causal analysis for breast cancer detectionMuhammad Zaheer Sajid, Muhammad Fareed Hamid, Imran Qureshi
Scientific Reports|December 5, 2025
EfficientPoseSegNet: a weakly supervised, attention-guided framework for human pose estimation, anatomical segmentation, and concealed object detection in backscatter millimeter-wave security screeningMuhammad Zaheer Sajid, Muhammad Fareed Hamid, Imran Qureshi, et al.
Frontiers in Oncology|April 23, 2026
Morphology-guided attention networks for explainable skin cancer detection under clinical uncertaintyMuhammad Zaheer Sajid, Muhammad Fareed Hamid, Zepa Yang, et al.
Diagnostics (Basel, Switzerland)|December 17, 2024
CAD-EYE: An Automated System for Multi-Eye Disease Classification Using Feature Fusion with Deep Learning Models and Fluorescence Imaging for Enhanced InterpretabilityMaimoona Khalid, Muhammad Zaheer Sajid, Ayman Youssef, et al.
SLAS Technology|July 18, 2025
An integrated deep learning framework using adaptive enhanced vision fusion and modified mobilenet architecture for precision classification of skin diseases with enhanced diagnostic performanceAhsan Bilal Tariq, Muhammad Zaheer Sajid, Nauman Ali Khan, et al.
Scientific Reports|May 19, 2026
A gated task-attentive multi-task network for unified retinal image analysisMuhammad Zaheer Sajid, Imran Qureshi, Muhammad Fareed Hamid, et al.
Frontiers in Medicine|January 1, 2026
An explainable deep learning-based feature fusion model for acute lymphoblastic leukemia diagnosis and severity assessmentHajra Khan, Muhammad Zaheer Sajid, Nauman Ali Khan, et al.
Diagnostics (Basel, Switzerland)|August 26, 2023
DR-NASNet: Automated System to Detect and Classify Diabetic Retinopathy Severity Using Improved Pretrained NASNet ModelMuhammad Zaheer Sajid, Muhammad Fareed Hamid, Ayman Youssef, et al.
Scientific Reports|May 21, 2026
An explainable multi-stage framework for brain tumor classification using hybrid feature fusion and EfficientNetB5 modelImran Qureshi, Muhammad Zaheer Sajid, Ayman Youssef, et al.
Pageof 1

Showing results (1-10 of 9) with videos related to

Sort By:
Pageof 1
Frontiers in Oncology|March 9, 2026
Explainable and uncertainty-aware ensemble framework with causal analysis for breast cancer detectionMuhammad Zaheer Sajid, Muhammad Fareed Hamid, Imran Qureshi
Scientific Reports|December 5, 2025
EfficientPoseSegNet: a weakly supervised, attention-guided framework for human pose estimation, anatomical segmentation, and concealed object detection in backscatter millimeter-wave security screeningMuhammad Zaheer Sajid, Muhammad Fareed Hamid, Imran Qureshi, et al.
Frontiers in Oncology|April 23, 2026
Morphology-guided attention networks for explainable skin cancer detection under clinical uncertaintyMuhammad Zaheer Sajid, Muhammad Fareed Hamid, Zepa Yang, et al.
Diagnostics (Basel, Switzerland)|December 17, 2024
CAD-EYE: An Automated System for Multi-Eye Disease Classification Using Feature Fusion with Deep Learning Models and Fluorescence Imaging for Enhanced InterpretabilityMaimoona Khalid, Muhammad Zaheer Sajid, Ayman Youssef, et al.
SLAS Technology|July 18, 2025
An integrated deep learning framework using adaptive enhanced vision fusion and modified mobilenet architecture for precision classification of skin diseases with enhanced diagnostic performanceAhsan Bilal Tariq, Muhammad Zaheer Sajid, Nauman Ali Khan, et al.
Scientific Reports|May 19, 2026
A gated task-attentive multi-task network for unified retinal image analysisMuhammad Zaheer Sajid, Imran Qureshi, Muhammad Fareed Hamid, et al.
Frontiers in Medicine|January 1, 2026
An explainable deep learning-based feature fusion model for acute lymphoblastic leukemia diagnosis and severity assessmentHajra Khan, Muhammad Zaheer Sajid, Nauman Ali Khan, et al.
Diagnostics (Basel, Switzerland)|August 26, 2023
DR-NASNet: Automated System to Detect and Classify Diabetic Retinopathy Severity Using Improved Pretrained NASNet ModelMuhammad Zaheer Sajid, Muhammad Fareed Hamid, Ayman Youssef, et al.
Scientific Reports|May 21, 2026
An explainable multi-stage framework for brain tumor classification using hybrid feature fusion and EfficientNetB5 modelImran Qureshi, Muhammad Zaheer Sajid, Ayman Youssef, et al.
Pageof 1