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I design, optimize, and integrate real-time object detection and tracking pipelines for NVIDIA Jetson, RK3588, and cloud environments — with measurable gains in FPS, latency, and deployment stability. From YOLO training to TensorRT optimization and production integration, I build Computer Vision systems that work reliably on real hardware. If you need more than just a trained model — if you need a working AI system integrated into hardware or software — I deliver complete, production-ready solutions. 🎯 WHAT I DELIVER • End-to-End Deep Learning Pipelines Model architecture → dataset optimization → training → evaluation → deployment • Real-Time Object Detection & Multi-Object Tracking Optimized YOLO pipelines with stable tracking (DeepSORT / ByteTrack / BOT-SORT) • ⚡ Edge AI Acceleration & Performance Optimization TensorRT conversion, CUDA acceleration, latency reduction, memory tuning, FPS improvements • 🔗 AI Integration into Production Systems Jetson deployment, inference APIs, embedded integration, debugging, monitoring & system optimization 🏆 PROVEN EXPERIENCE • 5★ Upwork reviews for NVIDIA Jetson Nano, AGX & Orin deployments • Deployed Frigate and real-time CV pipelines on Jetson Orin NX • Optimized inference performance using TensorRT for improved real-time execution • Installed and configured LLM environments with secure key management & usage tracking • Research & production AI deployment experience at HBrain 🛠 TECH STACK Deep Learning: PyTorch, CNN architectures, YOLO variants Computer Vision: OpenCV, real-time video processing, detection & tracking Optimization: TensorRT, CUDA Systems: Linux, Embedded Systems, NVIDIA Jetson Languages: Python, C++ If you share your hardware target, dataset sample, or performance goal, I can propose a clear technical architecture and realistic delivery plan.

7+ years as a Computer Vision Engineer and AI Product Engineer building production OCR, image analysis, segmentation, ONNX/FastAPI inference, VLM/RAG, and OpenAI/Claude/OpenClaw workflows. I help teams move from AI demos to reliable products: model pipelines, backend APIs, review dashboards, human approval gates, monitoring, cloud deployment, and clean handoff. My strongest projects combine: • Computer vision: segmentation, detection, landmarking, image analysis, visual inspection • OCR/document AI: extraction, validation, structured outputs, reviewer workflows • AI product systems: OpenAI/Claude, OpenClaw, VLMs, RAG, source traces, confidence checks • Production engineering: Python, FastAPI, ONNX, OpenCV, PyTorch/TensorFlow, PostgreSQL, Cloud Run/AWS I am a good fit when the output must be accurate, reviewable, logged, and safe enough for real business use.

Most computer vision projects fail not in training — but in deployment. Models that hit 95% accuracy in the lab break down when lighting shifts, hardware stutters, or the camera feed isn't clean. I build systems engineered to survive those conditions — and I've done it across industries, hardware platforms, and deployment environments. I'm a Computer Vision Engineer specializing in end-to-end AI pipelines — from raw camera input to real-time inference, deployed on edge hardware, cloud APIs, or both. ━━ Core services ━━ → Object detection & multi-object tracking — YOLOv8, YOLOv5, ByteTrack, BOTSort, MMDetection → Segmentation, pose estimation & keypoints — MediaPipe, custom model architectures → Edge AI deployment — NVIDIA Jetson Orin/Nano, Raspberry Pi, Hailo — TensorRT, ONNX, INT8/FP16 → Cloud & API deployment — FastAPI, Docker, AWS GPU instances, REST & WebSocket inference APIs → Video analytics & smart camera systems — safety monitoring, defect detection, zone tracking, people counting ━━ Systems I've shipped ━━ ✓ Real-time fall detection on NVIDIA Jetson — production-deployed, sub-100ms latency ✓ Zone-based people tracking & monitoring for safety-critical environments ✓ Industrial defect detection pipeline — TensorRT-optimized, running on constrained edge hardware ✓ End-to-end smart camera system: camera → inference → dashboard & real-time alerts ✓ OpenCV video analytics pipelines with custom pre/post-processing and business logic ━━ What makes my work different ━━ Most CV engineers deliver a model file. I deliver a working system — optimized, integrated, and running reliably in your environment. I lead a small team and personally own system architecture, optimization strategy, and core AI engineering on every project. You get senior-level technical execution, not delegation to juniors. Edge or cloud. Jetson or GPU server. Prototype or production scale. I've built across all of it. ━━ How a typical project runs ━━ 1. Discovery — review your hardware targets, data sources, and latency requirements before any code is written 2. Architecture — design the full pipeline: model selection, optimization path, deployment stack, integration points 3. Build & optimize — iterative development with benchmarked FPS and accuracy metrics at each stage 4. Deployment — containerized, documented, and running on your target environment 5. Handover — clean codebase, inline documentation, and a session so your team can maintain it independently ━━ Full tech stack ━━ Models: YOLOv8, YOLOv5, YOLOv7, MMDetection, Detectron2, PyTorch, TensorFlow, ONNX Runtime Tracking: ByteTrack, BOTSort, DeepSORT, StrongSORT, custom zone logic & counting algorithms Optimization: TensorRT INT8/FP16, ONNX quantization, model pruning, batch inference tuning Edge hardware: NVIDIA Jetson Orin/Nano, Raspberry Pi 4/5, Hailo-8, Coral TPU Cloud & infra: FastAPI, Flask, Docker, AWS EC2/Lambda, GCP, RTSP/RTMP stream processing Vision utilities: OpenCV, FFmpeg, GStreamer, PIL/Pillow, custom pipeline components ━━ Project types I take on ━━ → Greenfield CV systems — full pipeline from scratch to production deployment → Model optimization — take an existing model and make it production-fast on your hardware → Edge porting — migrate a cloud-based CV system to Jetson, Raspberry Pi, or Hailo → Pipeline debugging — diagnose and fix latency, accuracy, or stability issues in live systems → Inference API — wrap your CV model as a scalable, low-latency REST or WebSocket API → PoC → production — take a working demo and harden it for real-world deployment at scale → Team augmentation — embedded senior CV engineer for sprints or longer-term engagements ━━ Industries served ━━ Manufacturing & quality control — defect detection, visual inspection, production line monitoring Safety & security — real-time threat detection, perimeter monitoring, crowd analytics Retail & logistics — shelf analytics, people counting, queue management, warehouse tracking Healthcare — patient monitoring support systems, lab automation, medical imaging pipelines Agriculture — crop health detection, drone-based aerial inspection, field monitoring systems ━━ Common questions ━━ Work with our existing dataset? Yes — I assess quality, recommend augmentation strategies, and fine-tune models on your labeled data. Edge or cloud deployment? Both — Jetson, Raspberry Pi, and Hailo at the edge; AWS GPU instances and containerized APIs in the cloud. Can you take our prototype to production? That's one of my most common engagements — hardening, optimizing, and deploying existing concepts for real-world reliability. Documentation and handover included? Always. Clean code, inline comments, deployment instructions, and a dedicated handover session on every project. If you need computer vision that performs beyond lab conditions — on real hardware, with real data, in real-world environments — let's talk.

🔹 Top Rated Machine Learning Engineer | Expert in Detection, Tracking, Classification & OCR I specialize in building high-accuracy computer vision models — from object detection and classification to keypoint detection and OCR. With deep experience in YOLO (v8–v11), TensorFlow, and PyTorch, I’ve delivered results across industries including healthcare, logistics, and agriculture. 🚀 Highlighted Projects: 🔍 License Plate Recognition & Number Swapping — for Korean and Kazakh vehicles 🏥 COVID-19 & Viral Pneumonia Detection — 95%+ accuracy using X-ray images 🍎 Fruit Detection (Apple, Peach, Potato) — precision object detection with YOLO 📄 OCR & Keypoint Detection — paper/card ID localization and tracking 🏎️ Speed Estimation & Vehicle Tracking — model fusion using YOLO + Deep SORT ⚙️ Core Skills & Tools: YOLOv5/v8 | TensorFlow | PyTorch | OpenCV | ONNX Object Detection, Classification, OCR, Keypoint Detection High-speed model training on RTX 4080 Super As a Top Rated freelancer, I deliver clean, efficient, and production-ready models on time and with clear communication. Let’s bring your vision to life. 📩 Message me — I respond quickly and build fast.

33+ Successful Projects • 100% Job Success Top Rated 🎯 Computer Vision — YOLOv8/11, Faster R-CNN, U-Net, DeepLabV3+ 📍 Multi-Object Tracking — SORT, DeepSORT, ByteTrack 💬 LLM Applications — RAG, LangChain, Hugging Face, LoRA/QLoRA ⚡ Real-Time AI Deployment — OpenCV, PyTorch, TensorFlow 📈 Scalable Search — FAISS, vector DBs for face & document retrieval 🤖 LLM-Powered Telegram Bots — intelligent assistants & automation Why Work With Me 🟢 25+ successful projects with 100% Job Success (Top Rated) 🟢 Up to 90% automation through AI & workflow optimization 🟢 Scalable, production-grade systems (millions of records, real-time pipelines) 🟢 True end-to-end delivery — strategy → data → model → deployment 🟢 On-time delivery with measurable business impact 🟢 Clear, reliable communication throughout the project 📩 Message me for a free consultation — I’ll help you outline the best technical approach for your project.

Computer Vision Expert | YOLO | Object Detection | Tracking | OpenCV | Deep Learning | Jetson | Real-Time Systems | Image/Video Labeling Specialist | Machine Learning | OCR With 5+ years of experience and 150+ successful projects, I help businesses build high-performance Computer Vision and Deep Learning systems for real-world applications. I specialize in Object Detection, Multi-Object Tracking, Image Segmentation, and Real-Time Video Analytics, delivering scalable AI solutions used in production environments. 🚀 What I Can Do For You ✔ Build Object Detection systems (YOLOv8, YOLO11, YOLO26) ✔ Develop Multi-Object Tracking (DeepSORT, ByteTrack, BOT-SORT) ✔ Create Real-Time Video Analytics pipelines ✔ Design Image Segmentation models (U-Net, DeepLabV3+) ✔ Develop Face Recognition & Liveness Detection systems ✔ Build OCR & Document AI solutions ✔ Optimize models using TensorRT, CUDA, GPU acceleration ✔ Deploy AI systems via APIs, Docker, Cloud (AWS), Jetson ✔ Provide high-quality Image & Video Annotation / Labeling 👁 Core Expertise • Computer Vision • Deep Learning • Machine Learning • Object Detection • Image Segmentation • Multi-Object Tracking • OpenCV • YOLO (YOLOv8, YOLOv11, YOLOv26) • Real-Time AI Systems • Video Processing • OCR & Document AI • Data Annotation & Labeling 🧠 Real-World Solutions I Build • Surveillance & Smart Monitoring Systems • Retail Analytics & Customer Tracking • Face Recognition & Identity Verification • Industrial Defect Detection • Medical Image Analysis • Traffic & Vehicle Detection Systems ⚡ End-to-End Development I handle complete AI pipelines: Data Collection → Annotation → Model Training → Optimization → Deployment You get a fully production-ready system, not just a model. 🛠 Tech Stack 🔹 Deep Learning PyTorch, TensorFlow, Keras, CNN architectures, YOLO variants 🔹 Computer Vision OpenCV, MediaPipe, OCR systems, real-time video processing, detection and tracking pipelines 🔹 Machine Learning Scikit-learn, XGBoost, classification, regression, clustering 🔹 Tracking & Optimization DeepSORT, ByteTrack, SORT, TensorRT, CUDA 🔹 Backend & Deployment FastAPI, Flask, Docker, AWS, Jetson 🔹 Languages Python, C++ 💡 Why Clients Hire Me ✔ 150+ successful projects ✔ 100% Job Success (Top Rated) ✔ Real-time, high-performance systems ✔ Scalable & production-ready solutions ✔ Strong optimization (FPS, latency, memory) ✔ Clear communication & fast delivery 📌 Quick Overview 150+ Projects • 100% Job Success • Top Rated 🎯 Computer Vision — YOLOv8/11/26, Faster R-CNN, U-Net 📍 Tracking — DeepSORT, ByteTrack, BOT-SORT ⚡ Real-Time AI — OpenCV, PyTorch, TensorFlow 🧠 Deep Learning — CNNs, Vision Transformers 📄 OCR & Document AI — Tesseract, Google Document AI 🚀 Deployment — TensorRT, CUDA, Docker, AWS, Jetson 📩 Call to Action Looking to build a Computer Vision system, Object Detection model, or Real-Time AI solution? 👉 Send me a message — I’ll help you design the best approach and deliver a scalable, production-ready solution.