You will get a 3D object semantic segmentation model.
Rising Talent
Rising Talent
Project details
The objective of the project is to segment the objects from the 3d lidar mobile mapping data.
I used two models for training.
1) S3DIS
2) NPM3D
We got good results on S3DIS. We continue training on the S3DIS model. When we have the segmented data then we separate each object from the map. And after that, I used some post-processing to separate each object and create their
1) shape file
2) polygon
3) polyline.
4) camera-lidar fusion
Then upload the results to the ArcGIS map.
I used two models for training.
1) S3DIS
2) NPM3D
We got good results on S3DIS. We continue training on the S3DIS model. When we have the segmented data then we separate each object from the map. And after that, I used some post-processing to separate each object and create their
1) shape file
2) polygon
3) polyline.
4) camera-lidar fusion
Then upload the results to the ArcGIS map.
Machine Learning Tools
ArcGIS, Keras, NumPy, OpenCV, Python, Python Scikit-Learn, PyTorch, scikit-learn, SciPy, TensorFlowWhat's included
| Service Tiers |
Starter
$60
|
Standard
$1,000
|
Advanced
$4,000
|
|---|---|---|---|
| Delivery Time | 2 days | 10 days | 30 days |
Number of Revisions | Unlimited | Unlimited | Unlimited |
Model Validation/Testing | - | ||
Model Documentation | - | ||
Data Source Connectivity | - | - | |
Source Code | - | - |
About Muhammad
Senior Machine Learning & Generative AI Engineer | Azure | AWS | GCP
Rawalpindi, Pakistan - 10:39 am local time
I have 7+ years of experience designing, deploying, and scaling AI solutions across Azure, AWS, and GCP. I specialize in Generative AI, Agentic AI systems, Computer Vision (2D & 3D), forecasting, anomaly detection, OCR, and end-to-end MLOps pipelines.
I can take your project from idea → prototype → production deployment → scaling.
🤖 Generative AI, Agentic AI & LLM Systems
- I build intelligent AI systems capable of reasoning, automation, and real-world execution.
- ChatGPT-like assistants and enterprise AI copilots
- Agentic AI systems capable of autonomous reasoning and task execution
- Multi-agent workflows using LangChain, LangGraph, and Semantic Kernel
- Conversational AI and analytics agents connected to databases and APIs
- Retrieval-Augmented Generation (RAG) using vector databases (Qdrant, Pinecone, FAISS, ChromaDB)
- Intelligent document processing using LLMs (PDFs, invoices, reports)
- Integration with enterprise tools, APIs, and cloud systems
Technologies: OpenAI, Azure OpenAI, AWS Bedrock, Google Gemini, LLaMA
Result: Automate workflows, build intelligent agents, and extract insights from your data.
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👁️ Computer Vision (2D & 3D), Detection, Segmentation & Classification
- I build production-ready computer vision systems for real-world applications.
- Object detection using YOLO, Faster R-CNN, and custom models
- Image segmentation using U-Net, DeepLabV3, Mask R-CNN
- Image classification using CNNs, ResNet, EfficientNet, Vision Transformers (ViT)
- Real-time computer vision systems
- OCR and document intelligence systems
- 3D computer vision using point clouds, LiDAR, and spatial data
- 3D object detection, segmentation, and reconstruction
- Vision Transformer (ViT) and transformer-based vision systems
Technologies: PyTorch, TensorFlow, OpenCV, PyTorch3D, Open3D, ONNX
Result: Build intelligent vision systems capable of understanding images and 3D environments.
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📊 Machine Learning, Forecasting & Predictive Systems
- I develop machine learning systems that help businesses predict, detect, and optimize.
- Time-series forecasting (revenue, demand, business metrics)
- Anomaly detection systems for monitoring and alerting
- Predictive maintenance models
- Classification and regression models
- Feature engineering, model optimization, and evaluation
Result: Enable data-driven decision-making and automation.
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⚙️ MLOps, Cloud Deployment & Production Systems
- I deploy scalable AI systems on cloud platforms.
- Azure ML, AWS SageMaker, and GCP deployment
- CI/CD pipelines for ML systems
- Docker and Kubernetes deployment
- Real-time and batch inference systems
- Model monitoring, scaling, and automation
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Cloud Platforms:
Azure, AWS, GCP
Result: Reliable, scalable AI systems running in production.
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☁️ Data Engineering & AI Infrastructure
- Snowflake, PostgreSQL, BigQuery
- Vector databases and graph databases
- Automated data pipelines (Airflow, dbt, Azure Data Factory)
- Real-time and batch data processing
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🏆 Why Clients Choose Me
- 7+ years of real production experience
- Strong expertise in Azure, AWS, and GCP
- Expert in Generative AI, Agentic AI, and Computer Vision
- Experience building enterprise-scale AI systems
- Focus on production-ready, scalable solutions
- Clean, maintainable, professional code
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📈 Real-World Systems I Have Built
- AI agents and conversational AI systems
- Enterprise OCR systems are processing large document volumes
- Forecasting systems predicting business metrics
- Anomaly detection systems monitor operational data
- Computer vision systems for object detection and segmentation
- Cloud-deployed ML pipelines and production systems
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🎯 Industries I Have Worked With
- Finance
- Healthcare
- Retail & E-commerce
- Manufacturing
- AI startups and SaaS companies
- Computer Vision and Robotics
Steps for completing your project
After purchasing the project, send requirements so Muhammad can start the project.
Delivery time starts when Muhammad receives requirements from you.
Muhammad works on your project following the steps below.
Revisions may occur after the delivery date.
Annotation
trained weights