Hire the Best ImageJ Professionals

Imagine spending thousands of dollars training an AI model—only to realize the labels were flawed. That’s where I come in. I’m 𝐁𝐞𝐡𝐳𝐚𝐝 𝐀𝐥𝐢 𝐊𝐡𝐚𝐧 and co-founder of 𝐒𝐖𝐀𝐓𝐀𝐢, a data annotation and AI development platform trusted by AI startups and enterprises worldwide. With 4+ years of experience and a team of 178+ skilled annotators, I’ve personally led projects that helped train over 100 production-grade AI models from medical image segmentation, agriculture dataset annotations, AI-based electric poles condition monitoring system to autonomous vehicle perception systems. 🌐𝗪𝗵𝘆 𝗖𝗹𝗶𝗲𝗻𝘁𝘀 𝗧𝗿𝘂𝘀𝘁 𝗠𝗲: 𝗣𝗿𝗲𝗰𝗶𝘀𝗶𝗼𝗻-𝗟𝗲𝘃𝗲𝗹 𝗦𝗲𝗴𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻: I specialize in polygonal, pixel-wise and semantic segmentation with an obsessive attention to detail. 𝗔𝗜-𝗔𝘄𝗮𝗿𝗲 𝗔𝗻𝗻𝗼𝘁𝗮𝘁𝗶𝗼𝗻: Unlike generic labelers, I understand the AI pipeline. I don’t just label, I label for performance. Every dataset is annotated with model training, accuracy and edge-case handling in mind. 𝗘𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲-𝗦𝗰𝗮𝗹𝗲 𝗢𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝘀: Delivered $500,000+ worth of labeled data to top AI companies (like Moonvalley, SaharLabs etc) with proven systems for scalability, security and deadlines. 𝗖𝘂𝘀𝘁𝗼𝗺 𝗧𝗼𝗼𝗹𝘀, 𝗥𝗲𝗮𝗹 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻: Worked across CVAT, Labelbox, SuperAnnotate, Roboflow and even client-specific proprietary tools. 🌐𝗦𝘁𝗼𝗿𝘆 𝗼𝗳 𝗚𝗿𝗼𝘄𝘁𝗵: What began as a solo freelancing gig on Fiverr has now become a global agency delivering AI-ready data for some of the most innovative companies on Earth. Now offering our services on Upwork as well. 🛠️𝗦𝗲𝗿𝘃𝗶𝗰𝗲𝘀 𝗜 𝗢𝗳𝗳𝗲𝗿: ✦ Image & Video Segmentation (polygon, semantic, instance-based) ✦ Bounding Box, Keypoint & Landmark Annotation ✦ Text & Audio Annotation (multilingual available) ✦ Dataset Cleaning, Structuring & Preprocessing ✦ Consultancy on AI Dataset Design and Labeling Strategies ✦ AI Model Training and development Image annotation, Bounding boxes, 3D boxes, Video annotation, instance and semantic, Object labeling/tagging,Segmentation, Polygons masks, Text annotation, Line annotation, Key Points annotation, Cuboids, Image classification and categorization.

I specialize in image annotation and data labeling for AI and machine learning projects, with hands-on experience using tools such as CVAT, Roboflow, and LabelImg. I am skilled in bounding boxes, polygons, segmentation, image classification, dataset review, and accurate annotation based on project guidelines. I focus on delivering high-quality, consistent, and detail-oriented annotations to help improve AI model performance and training datasets. I am comfortable working with repetitive and precision-based tasks while maintaining accuracy and efficiency throughout the project. I am reliable, responsive to feedback, and committed to clear communication and on-time delivery. I welcome test tasks, trial projects, and long-term opportunities where I can contribute dependable annotation support and quality results.

I work at the intersection of scientific research, technical precision, and visual clarity. As an astrophysics researcher, I specialize in transforming complex concepts into publication-ready documents, high-impact visuals, and rigorously structured research outputs. My work is designed not just to meet academic standards, but to elevate the overall quality and presentation of your project. I collaborate with researchers, authors, and professionals who require accuracy, clarity, and refinement at a high level. What I deliver: Scientific Writing & Editing: Research papers, theses, and manuscripts with clear structure, strong argumentation, and publication-ready quality LaTeX Expertise: Clean, professional typesetting with precise formatting for journals, reports, and academic documents Data Visualization: High-quality graphs and analytical visuals that communicate insights effectively Technical Graphics & Design: Publication-grade diagrams, flowcharts, and figures built with precision and consistency My past work includes developing high-resolution visuals for scientific publications, constructing specialized research figures, and producing technical graphs for engineering applications. I prioritize detail, clarity, and reliability in every project. The goal is simple: deliver work that meets professional standards and strengthens the credibility of your research or presentation. If you are looking for someone who understands both the science and how to present it at a high level, I’m ready to collaborate.

With over 5 years of experience I specialize in annotating and labeling images for machine learning and AI applications. With a proven track record in creating accurate high-quality datasets across diverse domains.

High-quality AI training data can make or break your model. I help AI/ML teams scale data annotation with 95–99% accuracy, backed by structured QA workflows and reliable turnaround, across image, text, and audio datasets. If you're building computer vision or NLP models, I ensure your data is clean, consistent, and production-ready. 1. Experience handling large-scale datasets (10K to 1M+ annotations) 2. Multi-level QA pipelines (review, sampling, audits) 3. Expertise across CV, NLP, Geospatial, and ADAS use cases With 5+ years of experience in AI training data, I’ve consistently delivered high-accuracy datasets with fast turnaround and scalable workflows. I also provide access to multilingual annotation teams (German, Spanish, French, Portuguese, Japanese, etc.), enabling global dataset support. What I can help you with: • Image Annotation (Bounding Boxes, Segmentation, Tagging) • Text Annotation (Classification, Sentiment Analysis, NLP Tasks) • Audio Annotation (Event Labeling, Timestamping) • Data Validation & Quality Assurance I operate with a trained and scalable team of annotators, allowing me to handle both small pilot tasks and large-volume projects efficiently. Why clients choose to work with me: • 95–99% accuracy with strong QA systems • Structured workflows and clear communication • Ability to scale quickly based on project needs • On-time delivery with consistent quality I’m available to start immediately and open to both pilot tasks and long-term collaborations. I’m happy to start with a small sample or pilot task to demonstrate quality before scaling.

Most machine learning projects fail between the prototype and production. I've shipped 47+ that didn't. 🎯 YOLO Detection | 🧍 Pose Estimation | 🏋️ Sports AI | 🛒 Retail AI | 🛡️ CCTV Analytics | 🔄 Tracking | 🧠 ML Pipelines | 🤖 AI Agents | 💬 LLM Integration 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. Object detection · Machine learning · Pose estimation · Multi-camera tracking · Segmentation · Re-identification · Anomaly detection · OCR & ANPR · Optical flow · Depth estimation · LLM-powered reasoning · Agentic decision pipelines While most CV engineers stop at training the model, I go further: → Accelerated inference with TensorRT, ONNX, OpenVINO, and FP16/INT8 quantization (up to 5× faster) → LLM agents layered over CV pipelines for real-time decisions, alerts, and natural language outputs → Mobile deployment via CoreML (iOS) and TFLite (Android) with 10+ live apps shipped → Edge deployment on Jetson, OpenVINO, Apple Neural Engine, and CUDA/cuDNN → End-to-end pipeline: camera input → training → optimization → real-time actionable output Key Accomplishments: ⭐ Generated $5M+ in client revenue ⭐ Delivered 100+ end-to-end computer vision systems ⭐ Successfully launched my own 2 SaaS products ⭐ Real-time sports AI for 7+ sports, improving analytics for 15+ teams ⭐ Mobile AI on iOS (Core ML) & Android (TFLite), powering 10+ apps ⭐ Surveillance, safety, and industrial AI solutions ⭐ Medical imaging AI for 5+ hospitals: tumor detection, ultrasound, test strips ⭐ Model optimization: up to 5× faster inference using FP16/INT8, ONNX, TensorRT, OpenVINO ⭐ Multi-object tracking, re-identification, Model Training 1M+ labelled Dataset ⭐ Agentic CV systems that perceive, reason, and act without human input in the loop 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: - Sports & Fitness: athlete tracking, shot detection, scoring automation, drill analysis, pose estimation - Industrial & Workplace: tire defect inspection, PPE compliance, staff monitoring, meter reading, machine vision inspection, automated quality control - Surveillance & Security: ANPR, crowd monitoring, people counting, animal attack detection, exam cheating detection, perimeter security, intrusion detection - Healthcare & Medical: tumor detection, ultrasound processing, test strip analysis, X-ray/CT scan processing, lesion segmentation, medical image annotation - Traffic & Transport: aerial monitoring, traffic flow AI, license plate recognition, vehicle detection, accident detection, parking management - Retail & Business: customer analytics, receipt extraction, retail intelligence, object recognition, shelf monitoring, inventory management Tech Stack: Machine Learning, Deep Learning, YOLOv5, YOLOv8 - YOLO26, Detectron2, DeepSORT, StrongSORT, MMDetection, MediaPipe, OpenPose, PoseTrack, Action Recognition, Semantic Segmentation, Instance Segmentation, OCR, Anomaly Detection, Motion Detection, Object Counting, License Plate Recognition, PyTorch, TensorFlow, TensorFlow Lite, Keras, OpenCV, FastAPI, Flask, Core ML, TFLite, ONNX, TensorRT, OpenVINO, CUDA, Swift, Kotlin, Flutter, Python, C++, AWS, GCP, Azure, Edge Deployment, Mobile AI, Real-Time Inference, Surveillance AI, Aerial Drone Analytics, Video Stream Analytics, AI Automation, LLM Integration (GPT-4o, Claude, Gemini, Groq), AI Agent Frameworks (LangChain, LangGraph, CrewAI), RAG Pipelines, Streaming LLM Inference license plate recognition, aerial drone analytics, surveillance AI, mobile AI, embedded systems, deep learning pipelines, inference optimization, video stream analytics, AI automation, AI for industry 4.0, computer vision pipelines. 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.