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I specialize in Computer Vision and Machine Learning systems that detect, recognize, classify, and extract information from images and video. Whether the goal is identifying objects in real-time footage, extracting text from documents, tracking movement across camera feeds, or building custom visual AI models, I focus on creating solutions that perform reliably beyond controlled test environments. Most images and video contain valuable information, but turning that visual data into something a machine can reliably understand is where the real challenge begins. My background combines machine learning, deep learning, and practical software engineering, allowing me to take projects from dataset preparation and model training all the way to deployment and optimization. Areas I Work In: • Object Detection & Tracking (YOLO) • Computer Vision Applications (OpenCV) • OCR & Document Intelligence • Image Classification • Image Segmentation • Video Analytics • Face Detection & Recognition • Visual Inspection Systems • Custom Deep Learning Models • Machine Learning & AI Solutions Technical Stack: • Python • YOLO • OpenCV • PyTorch • TensorFlow • Scikit-Learn • EasyOCR • Tesseract • FastAPI • Docker • REST APIs What I Can Help You Build: Object Detection Systems, Custom-trained detection models capable of identifying, counting, and tracking objects in images or video streams for surveillance, industrial monitoring, retail analytics, sports analytics, and other specialized applications. OCR & Document Processing, Automated extraction of structured information from invoices, forms, receipts, reports, IDs, and scanned documents using OCR and document intelligence pipelines. Image Classification & Segmentation, Models that classify images into meaningful categories or isolate specific regions and objects for further analysis. Video Analytics, Real-time processing pipelines that analyze camera feeds, monitor activity, track movement, and generate actionable insights from video data. End-to-End Machine Learning Pipelines, Dataset preparation, annotation, model training, evaluation, optimization, deployment, and integration into existing applications or workflows. Example Projects: • Custom YOLO-based object detection models trained for industry-specific requirements • OCR systems for extracting and validating structured document data • Image classification models for automated visual categorization • Real-time video analysis and tracking systems • Deep learning solutions built for specialized computer vision challenges I pay particular attention to model performance under real-world conditions, including difficult lighting, camera angles, motion blur, occlusion, and dataset imbalance. A model that performs well in production requires more than high benchmark accuracy—it requires careful evaluation, testing, and optimization. If you're working on a computer vision problem and need a reliable engineering solution rather than just a proof of concept, feel free to reach out. Share your use case, available data, or project goals, and we'll determine the best technical approach together. Talha

Most Machine Vision projects fail between the prototype and production. I've shipped 54+ that didn't. ⚙️YOLO Detection | Pose Estimation | Object Tracking | AI Agents | LLM Integration Sports & Fitness AI | CCTV & Surveillance AI | Retail AI | Healthcare AI You have a working concept... or a clear problem involving cameras, video, or image data. The challenge is making it fast, accurate, and stable under real-world conditions. Wrong framework choices. Inference too slow for live video. Models that break the moment lighting, angle, or environment changes. And systems that detect things but can't reason about them or act on them autonomously. That's exactly where most builds stall. I design and build real-time computer vision pipelines that go all the way... from model training to live deployment... and increasingly, from visual perception to autonomous AI agents that understand, decide, and narrate. LLM APIs (OpenAI, GPT-4o, Gemini, Claude) | AWS (EC2, S3, Lambda) | Azure Cloud Services | MLOps & API Integration | Model Deployment & Scaling While most CV engineers stop at training the model, I go further: → High-speed inference optimization using TensorRT, ONNX, OpenVINO, FP16/INT8 (up to 5× faster) → LLM agents integrated with vision pipelines for alerts, reasoning, and automation → Mobile AI deployment using Core ML (iOS) and TFLite (Android) with 10+ shipped apps → Edge AI deployment on Jetson, OpenVINO, CUDA, and embedded systems → End-to-end pipelines: data → training → optimization → real-time deployment Key Accomplishments: ⭐ $5M+ revenue from AI solutions ⭐ 100+ computer vision systems delivered ⭐ Built and launched 2 SaaS products ⭐ Real-time sports AI (7+ sports, 15+ teams) ⭐ 10+ mobile AI apps (iOS Core ML, Android TFLite) ⭐ Production AI for surveillance, industrial & safety use cases ⭐ Medical imaging AI deployed in 5+ hospitals ⭐ Up to 5× faster inference (ONNX, TensorRT, FP16/INT8) ⭐ Large-scale tracking & re-ID (1M+ labeled data) ⭐ Agentic AI systems for autonomous decision-making If you have read this far, please note that I appreciate you taking the time to learn about me. Personally, it’s been an amazing journey and knowledge exercise to get to this level of competence in AI and software development. Domain Expertise: ✅ athlete tracking | shot detection | scoring | drill analysis | pose estimation ✅ defect inspection | PPE compliance | staff monitoring | meter reading | quality control ✅ ANPR | crowd monitoring | people counting | intrusion detection | perimeter security ✅ tumor detection | ultrasound | X-ray/CT analysis | lesion segmentation | medical imaging ✅ aerial monitoring | traffic flow | license plate recognition | vehicle & accident detection ✅ customer analytics | receipt extraction | shelf monitoring | inventory tracking Tech Stack: YOLOv5–YOLOv8–YOLOv11, Detectron2, MMDetection, DeepSORT, StrongSORT, MediaPipe, OpenPose, Pose Estimation, Action Recognition, Segmentation (semantic & instance), OCR, anomaly detection, object tracking, PyTorch, TensorFlow, TFLite, Core ML, OpenCV, FastAPI, Flask, ONNX, TensorRT, OpenVINO, CUDA, AWS, Azure, GCP, edge AI, mobile AI, real-time inference, video analytics, AI automation, LLM integration (GPT-4o, Claude, Gemini, Groq), LangChain, LangGraph, CrewAI, RAG systems. 💬 If your project involves cameras, video, or images... and you need it fast, accurate, fully deployed, and intelligent enough to reason and act autonomously... I am the engineer you are looking for.

Hi, I'm Zeeshan 👋 Give me something to build and i'll build it so it works for you 24/7. Thats my promise! If you shoot me a invitation or message ill send you a personalised loom video back on how i may be able to help you!... I’m a Computer Vision & Document AI Engineer with more than half a decade of experience building production-grade image and video intelligence systems not demos, not notebooks. My core expertise is image processing and computer vision, especially where data is messy, multilingual, scanned, or operationally constrained. What I Actually Build: 1. OCR & Document Image Processing I design end-to-end OCR pipelines for real-world documents: Urdu & English OCR (printed + complex layouts) Preprocessing: binarization, skew correction, denoising, layout analysis Text detection & bounding-box post-processing Tesseract, custom deep-learning OCR, Pix2Text Searchable archives using FAISS & vector indexing 2. Computer Vision for Images & Video I build vision systems that generate usable metadata: Object detection, tracking, segmentation (YOLO-based pipelines) Video-to-metadata systems for analytics and downstream automation Image classification and visual feature extraction High-performance OpenCV + PyTorch pipelines 3. Vision-Driven AI Applications When needed, I wrap CV systems into clean, usable products: Flask / FastAPI backends for vision services OCR-powered document portals Image & video search using embeddings RAG pipelines only where they add real value I’m a strong fit if you need image processing, OCR, or computer vision systems that must actually work in production especially for scanned documents, archives, or video data. EXPERTISE: AI Automation | Computer Vision | Sports Analysis | Image Processing | OCR | Mediapipe | Landmarks detection | Object Detection | Object Classification | Doucment Automation | Deep Learning | RAG | Tensorflow | PyTorch | Sign Language Production | GANs | Diffusion Models | Vision Transformers

I’m a Machine Learning Engineer specializing in Computer Vision, Deep Learning, Python, NLP, and AI development. I build practical AI solutions that help businesses, startups, and research teams automate processes, analyze data, and solve real-world problems. I have hands-on experience developing and training machine learning and deep learning models, working with datasets, preprocessing data, evaluating models, and building AI applications using Python and modern ML frameworks. What I Can Help You With Machine Learning & Deep Learning • Machine learning model development • Classification and regression • Predictive modeling • Feature engineering • Model training and evaluation • CNN and deep learning models • Model optimization and fine-tuning Computer Vision • YOLO object detection • Image classification • Semantic segmentation • Image preprocessing • OpenCV development • Medical image analysis • Satellite image analysis • Virtual try-on and body-part detection NLP & Generative AI • NLP applications • AI chatbots • LLM integration • Prompt engineering • Text classification and analysis • Document-based AI solutions • RAG applications • AI automation Python & AI Development • Python development • PyTorch • TensorFlow • Scikit-learn • OpenCV • Pandas & NumPy • REST API integration • FastAPI • Git & GitHub Selected AI & Machine Learning Projects YOLOv8 Body-Part Detection for Virtual Try-On Developed a custom YOLOv8 computer vision model to detect upper-body and lower-body regions from human images for a virtual try-on application. Satellite Image Semantic Segmentation Developed a deep learning segmentation system for identifying roads, buildings, vegetation, and water bodies from satellite imagery. Brain Tumor Detection from MRI Built a CNN-based deep learning model for classifying brain MRI images for tumor detection. AI-Powered Sentiment Analysis Developed a sentiment analysis application for analyzing text and presenting insights through an interactive dashboard. Voice-Based German Translator Built a voice-based translation application combining speech recognition, NLP, and language translation. Machine Learning Stock Market Analysis & Prediction Developed machine learning models for analyzing historical market data and generating predictive insights. Why Work With Me? • Strong focus on solving the actual business or research problem • Clean and structured Python development • Practical machine learning and deep learning experience • Clear communication throughout the project • Reliable and organized workflow • Willingness to understand requirements before implementation • Support with testing, debugging, and improvements Whether you need a machine learning model, computer vision system, deep learning solution, NLP application, AI chatbot, or Python-based AI application, I can help turn your requirements into a practical solution. Send me your project requirements and let’s discuss the best AI approach for your problem.

With 20+ years of industry experience (10+ years in embedded systems), I build high-performance real-time video and computer vision solutions. I specialize in: RTSP, WebRTC, and low-latency streaming GStreamer, FFmpeg, OpenCV pipelines Embedded Linux development (Raspberry Pi, Orange Pi, Jetson) Multi-camera systems, video recording, and synchronization AI-based video analytics (YOLO, RKNN, edge AI) I have delivered production-grade systems including: Real-time multi-camera streaming and recording platforms AI-powered video analytics solutions Embedded vision systems with hardware acceleration End-to-end video pipelines (capture → process → encode → stream) My focus is always on performance, reliability, and scalability — especially in resource-constrained embedded environments. If you need a practical expert who can bridge camera hardware, video pipelines, and real-world deployment, I can help.

I build computer vision systems that actually work in production, not just in a Jupyter notebook demo. I've handled CV projects end to end: raw dataset, trained model, deployed API. If you need a proof of concept in two weeks or a full production pipeline, I can scope it clearly and deliver on time. What I work on: Object Detection & Tracking (YOLOv8, Faster R-CNN, DETR) Image Segmentation (SAM, Mask R-CNN, U-Net) Medical Imaging & Diagnostics (X-ray, MRI, pathology slide analysis) Real-Time Video Processing & Edge Deployment (ONNX, TensorRT, OpenCV) Custom Dataset Creation, Annotation Pipelines & Model Fine-Tuning Industrial Visual Inspection & Defect Detection Tech stack: Python, PyTorch, TensorFlow, OpenCV, Roboflow, HuggingFace, FastAPI, Docker If your project involves cameras, images, or video, message me and let's talk about what you're building. (ignore this line, for search only): computer vision developer, YOLOv8 expert, object detection engineer, image segmentation freelancer, PyTorch developer, OpenCV expert, medical imaging AI, real time video processing, edge AI deployment, TensorRT ONNX developer