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MOHAMMAD MOHIUDDIN .

Assistant Professor

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mmazad@ju.edu.sa
Computer and Information Sciences - Computer and Information Sciences College
Collage
Computer and Information Sciences College
كلية علوم الحاسب والمعلومات
Department
Computer Science
علوم الحاسب
Researches
22
22
Page Visits
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Current courses

Recent courses

Fm researches

Last Researches

A novel ensemble learning method using majority based voting of multiple selective decision trees
MOHAMMAD MOHIUDDIN AZAD
Advancing Cephalometric Soft-Tissue Landmark Detection: An Integrated AdaBoost Learning Approach Incorporating Haar-Like and Spatial Features
MOHAMMAD MOHIUDDIN AZAD
A Health Monitoring System Using IoT-Based Android Mobile Application
MOHAMMAD MOHIUDDIN AZAD

fm info

Researches

A novel ensemble learning method using majority based voting of multiple selective decision trees
MOHAMMAD MOHIUDDIN AZAD
Advancing Cephalometric Soft-Tissue Landmark Detection: An Integrated AdaBoost Learning Approach Incorporating Haar-Like and Spatial Features
MOHAMMAD MOHIUDDIN AZAD
A Health Monitoring System Using IoT-Based Android Mobile Application
MOHAMMAD MOHIUDDIN AZAD
Applications of Depth Minimization of Decision Trees Containing Hypotheses for Multiple-Value Decision Tables
MOHAMMAD MOHIUDDIN AZAD
Robustness Fine-Tuning Deep Learning Model for Cancers Diagnosis Based on Histopathology Image Analysis
MOHAMMAD MOHIUDDIN AZAD
Decision Trees with Hypotheses
MOHAMMAD MOHIUDDIN AZAD
An Enhanced Machine Learning Approach for Brain MRI Classification
MOHAMMAD MOHIUDDIN AZAD
RTF-RCNN: An Architecture for Real-Time Tomato Plant Leaf Diseases Detection in Video Streaming Using Faster-RCNN
MOHAMMAD MOHIUDDIN AZAD
Prediction of Offshore Wave at East Coast of Malaysia-A Comparative Study
MOHAMMAD MOHIUDDIN AZAD
A Computational Tool for Detection of Soft Tissue Landmarks and Cephalometric Analysis
MOHAMMAD MOHIUDDIN AZAD
A Precise Medical Imaging Approach for Brain MRI Image Classification
MOHAMMAD MOHIUDDIN AZAD
A Bi-criteria Optimization Model for Adjusting the Decision Tree Parameters
MOHAMMAD MOHIUDDIN AZAD
Decision Rules Derived from Optimal Decision Trees with Hypotheses
MOHAMMAD MOHIUDDIN AZAD
Maximum Entropy Markov Model for Human Activity Recognition Using Depth Camera
MOHAMMAD MOHIUDDIN AZAD
Minimizing Number of Nodes in Decision Trees with Hypotheses
MOHAMMAD MOHIUDDIN AZAD
Minimizing Depth of Decision Trees with Hypotheses
MOHAMMAD MOHIUDDIN AZAD
Optimization of Decision Trees with Hypotheses for Knowledge Representation
MOHAMMAD MOHIUDDIN AZAD
Entropy-Based Greedy Algorithm for Decision Trees Using Hypotheses
MOHAMMAD MOHIUDDIN AZAD
Sorting by Decision Trees with Hypotheses
MOHAMMAD MOHIUDDIN AZAD
Decision Trees with at Most 19 Vertices for Knowledge Representation
MOHAMMAD MOHIUDDIN AZAD
Representation of Knowledge by Decision Trees for Decision Tables with Multiple Decisions
MOHAMMAD MOHIUDDIN AZAD
Decision Trees for Knowledge Representation
MOHAMMAD MOHIUDDIN AZAD

Education

Ph.D.
king abdullah university of science and technology - Computer Science
2018 - 2012

Projects

Development of a digital software to investigate the soft tissue profile of Saudi patients for orthodontic treatment
2020 - 2022

Certifications

Best Contributed Paper Award
2016 - 2016
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