Muhammad Faisal S.

🌟 Computer Vision & Deep Learning Engineer | YOLO Specialist | Smart City & Road Asset AI Solutions I am a Computer Vision & Deep Learning Engineer with specialized expertise in building YOLO-based object detection, segmentation, and classification models, particularly for civil engineering, road infrastructure, and smart city applications. My work focuses on transforming raw image/video data into actionable insights through advanced AI solutions—helping organizations improve transportation safety, automated inspections, and infrastructure monitoring. 🔧 Core Expertise 🚀 YOLO Object Detection & Segmentation • Custom training, fine-tuning, and deployment • Specialized in civil engineering datasets 🛣️ Road Asset Detection & Tracking • Traffic signs, lane markings, curbstones, light poles, manholes, and more • Automatic asset inventory generation from images/videos 🕳️ Pavement & Crack Detection • Segmentation & classification of cracks (longitudinal, transverse, alligator, block, raveling, weathering) 🚗 Traffic Analysis • Vehicle detection, counting, speed estimation & classification (CCTV/dashcam) 🗑️ Waste & Garbage Detection • Smart monitoring systems for urban management & cleanliness 🖼️ Image Processing & Preprocessing • Dataset cleaning, annotation, augmentation, and model optimization 🛠️ Tools & Technologies Deep Learning: YOLOv5, YOLOv7, YOLOv8, TensorFlow, PyTorch Image Processing: OpenCV, Scikit-image, PIL Annotation Tools: LabelImg, CVAT, Roboflow Programming: Python (Pandas, NumPy, Matplotlib) 🌟 Personal Qualities ✨ Strong problem-solving mindset ✨ Detail-oriented and quality-driven ✨ Clear communication & quick response time ✨ Passionate about real-world AI innovations ✨ Always eager to take on challenging projects