Ahmed M.

With over 6 years of experience in delivering cutting-edge computer vision solutions , I specialize in a wide range of services:

1. Image Classification

Mastery in building state-of-the-art image classification models using CNNs, transfer learning, and data augmentation ?.

*Key project*: Alpaca Image Classification with MobileNetV2, achieving an impressive 93% accuracy.

2. Object Detection

Expertise in developing models to detect and localize objects within images ️, utilizing frameworks like YOLO, SSD, and Faster R-CNN.

3. Semantic Segmentation

Skilled in pixel-wise classification for tasks like roadway damage detection ️, leveraging architectures such as U-Net, DeepLab, and Mask R-CNN.

4. OCR (Optical Character Recognition)

Developed advanced OCR systems capable of recognizing Arabic text from images and screenshots , integrated into AI systems for seamless text conversion and processing.

5. Diacritic Restoration in Arabic Text

Created 'Tashkeel' ️, an AI-powered solution that uses OCR to process Arabic text and automatically add diacritics.

6. Facial Recognition & Analysis

Proficient in facial detection, recognition, and emotion analysis , for applications in security and customer engagement.

7. Medical Imaging

Experience in healthcare-related projects like Breast Cancer Detection , employing CNNs and transfer learning to classify medical images.

8. Vision-Language Models (VLMs)

Expertise in implementing and integrating vision-language models into low-code/no-code platforms for web and app development .

9. Anomaly Detection

Advanced knowledge in detecting defects, abnormalities, or irregularities ️, across industries like infrastructure and manufacturing.

10. Data Annotation & Preparation

Skilled in curating datasets, annotating images ️, and applying data preprocessing techniques like augmentation to build robust computer vision models.

I work as a lecturer in the field of computer vision on various platforms , where I explain the roadmap to this field from start to finish ️. I also provide hands-on practical applications ️, using both visual ️ and auditory learning methods.

Technical Skills:

1. Programming Languages

- Proficiency in Python and libraries like OpenCV, TensorFlow, Keras, PyTorch, and NumPy.

2. Machine Learning & Deep Learning

- Strong knowledge of algorithms, CNNs, RNNs, transfer learning, and backpropagation techniques.

3. Image Processing

- Expertise in image enhancement, filtering, edge detection, segmentation, and feature extraction.

4. Object Detection & Recognition

- Familiarity with frameworks like YOLO, SSD, Faster R-CNN for detecting and recognizing objects in images.

5. Neural Network Architectures

- Mastery in CNNs, RNNs, U-Net, ResNet, and MobileNet for image classification and segmentation.

6. Data Handling & Preprocessing

- Skills in data annotation, augmentation, and preprocessing techniques to prepare datasets for training.

7. Computer Vision Algorithms

- Understanding of feature extraction techniques (SIFT, SURF, HOG), optical flow, and 3D reconstruction.

8. Optimization & Deployment

- Knowledge of model optimization techniques and deployment on edge devices or cloud environments (TensorRT, ONNX).

Tutoring & Mentorship Skills:

1. Curriculum Development

- Ability to design a comprehensive roadmap , covering beginner to advanced concepts in computer vision.

2. Effective Communication

- Excellent verbal and written communication skills to explain complex topics in a clear, engaging manner .

3. Practical Application & Hands-on Learning

- Expertise in guiding students through hands-on coding sessions and real-world projects ️.

4. Visualization & Teaching Tools

- Use of visual aids, diagrams, and interactive learning methods for both auditory and visual learners .

5. Problem-Solving & Critical Thinking

- Ability to teach problem-solving approaches for computer vision challenges, encouraging indep