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Ahmed Taha

Ahmed Taha

AI Data Preprocessing and Classification - Alzheimer's Detection Project

Egypt flagCairo, Egypt
$20.00/hrEntry LevelInternal Proprietary Tooling

Key Skills

Software

Internal/Proprietary Tooling

Top Subject Matter

Medical/dicom Domain Expertise
Hand gesture recognition/Sign Language

Top Data Types

ImageImage

Top Task Types

Classification

Freelancer Overview

AI Data Preprocessing and Classification - Alzheimer's Detection Project. Brings 4+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include TensorFlow. Education includes Bachelor of Science, Benha University (2024). AI-training focus includes data types such as Image and labeling workflows including Classification.

Entry LevelEnglishArabic

Labeling Experience

AI Data Preprocessing and Classification - Alzheimer's Detection Project

ImageClassification
I built a deep learning model for early Alzheimer’s detection using MRI images, applying data preprocessing and augmentation to improve performance. This required preparing labeled image datasets for model training and evaluation. The role focused on managing medical images, ensuring data quality, and classifying MRI scans for Alzheimer’s detection. • Prepared and annotated medical image datasets for deep learning. • Performed data preprocessing, including normalization and augmentation. • Ensured image data quality and consistency for accurate model training. • Facilitated machine learning classification of MRI scans for early disease detection.

I built a deep learning model for early Alzheimer’s detection using MRI images, applying data preprocessing and augmentation to improve performance. This required preparing labeled image datasets for model training and evaluation. The role focused on managing medical images, ensuring data quality, and classifying MRI scans for Alzheimer’s detection. • Prepared and annotated medical image datasets for deep learning. • Performed data preprocessing, including normalization and augmentation. • Ensured image data quality and consistency for accurate model training. • Facilitated machine learning classification of MRI scans for early disease detection.

2023 - 2024

Medical Image Annotation and Classification - Oral Cancer Detection

ImageClassification
I developed a DenseNet201-based model for oral cancer detection, which involved handling and organizing medical images labeled for diagnostic purposes. Tasks included data preprocessing, transfer learning, and accurate annotation for model training. This ensured reliable classification of medical images for cancer detection. • Managed and preprocessed a dataset of 4,500+ labeled medical images. • Labeled cancerous and non-cancerous categories for supervised learning. • Utilized transfer learning for model improvement. • Ensured data integrity and accuracy in diagnostic image classification.

I developed a DenseNet201-based model for oral cancer detection, which involved handling and organizing medical images labeled for diagnostic purposes. Tasks included data preprocessing, transfer learning, and accurate annotation for model training. This ensured reliable classification of medical images for cancer detection. • Managed and preprocessed a dataset of 4,500+ labeled medical images. • Labeled cancerous and non-cancerous categories for supervised learning. • Utilized transfer learning for model improvement. • Ensured data integrity and accuracy in diagnostic image classification.

2023 - 2023

Image Classification and Annotation - ASL Recognition Project

ImageClassification
I implemented and trained CNN and transfer learning models for American Sign Language recognition on labeled hand gesture datasets. My work included labeling, preprocessing, augmentation, and normalization of over 2,500+ images. The main focus was boosting model accuracy through careful preparation of classified image data. • Labeled and organized hand gesture image datasets for model training. • Applied preprocessing, normalization, and data augmentation techniques. • Enhanced dataset quality to support effective CNN training. • Achieved high model accuracy for ASL gesture recognition through precise classification.

I implemented and trained CNN and transfer learning models for American Sign Language recognition on labeled hand gesture datasets. My work included labeling, preprocessing, augmentation, and normalization of over 2,500+ images. The main focus was boosting model accuracy through careful preparation of classified image data. • Labeled and organized hand gesture image datasets for model training. • Applied preprocessing, normalization, and data augmentation techniques. • Enhanced dataset quality to support effective CNN training. • Achieved high model accuracy for ASL gesture recognition through precise classification.

2023 - 2023

Education

B

Benha University

Bachelor of Science, Computer Science and Artificial Intelligence

Bachelor of Science
2020 - 2024

Work History

D

DEY - Creativa Innovation Hubs

Freelance Data Analyst

Cairo
2026 - Present
N

National Telecommunication Institute

AI & ML Trainee

Cairo
2023 - 2023