You will get Custom Computer Vision Model for Object Detection or Classification
Project details
Off-the-shelf AI models are trained on generic data — they don't know your products, your environment, or your specific edge cases. A custom-trained model does.
I build computer vision models tailored to your exact detection or classification task, from dataset preparation and model training to deployment on your target hardware. Whether you need real-time object detection on a cloud server, a defect classifier on a production line, or a gesture recognition system on an edge device — I design the full pipeline to match your performance and hardware requirements.
Every model is trained using industry-standard frameworks including PyTorch, YOLO, and TensorFlow, and delivered with evaluation metrics, exported model files, and deployment documentation.
I have built and deployed real-time computer vision systems on edge hardware including smart glasses, with experience in multimodal fusion and LLM integration on top of vision pipelines — bringing both research depth and practical deployment experience to your project.
I build computer vision models tailored to your exact detection or classification task, from dataset preparation and model training to deployment on your target hardware. Whether you need real-time object detection on a cloud server, a defect classifier on a production line, or a gesture recognition system on an edge device — I design the full pipeline to match your performance and hardware requirements.
Every model is trained using industry-standard frameworks including PyTorch, YOLO, and TensorFlow, and delivered with evaluation metrics, exported model files, and deployment documentation.
I have built and deployed real-time computer vision systems on edge hardware including smart glasses, with experience in multimodal fusion and LLM integration on top of vision pipelines — bringing both research depth and practical deployment experience to your project.
AI Development Type
Deep Learning, Knowledge Representation, Model Tuning, Recommendation System, Software MaintenanceAI Tools
Keras, NVIDIA AI Platform, OpenCV, PyTorch, TensorFlowAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$5
|
Standard
$10
|
Advanced
$15
|
|---|---|---|---|
| Delivery Time | 1 day | 3 days | 5 days |
Number of Revisions | 1 | 2 | 6 |
AI Model Integration | - | - | - |
Detailed Code Comments | - | - | - |
Knowledge Graph | - | - | - |
Model Documentation | - | - | - |
Ontology | - | - | - |
Source Code | - | - | - |
Taxonomy | - | - | - |
Frequently asked questions
About Lawrence
AI Consultant | Computer Vision, Deep Learning & Agent Implementation
Chang-hua, Taiwan - 8:16 pm local time
I am an AI consultant and developer with hands-on experience in computer vision, deep learning, and agentic AI systems. My focus is not just on building — I help clients understand what they need, design the right approach, and ensure their team can use and maintain it confidently.
What I work on:
👁️ Computer Vision & Deep Learning: Object detection, image classification, pose estimation, and custom model training using YOLO, MediaPipe, PyTorch, and TensorFlow. I have built real-time recognition systems deployed on edge devices.
🤖 AI Agent Development: I design and build intelligent agents that reason and complete multi-step tasks using LangGraph, CrewAI, AutoGen, and Model Context Protocol (MCP) — from single-agent pipelines to multi-agent supervisor architectures.
🗺️ AI Implementation Planning: I help businesses identify the right AI use cases, select the correct tech stack, and design a clear adoption roadmap — so you invest in the right solution from day one.
🎓 AI Application Training: I provide practical training sessions and structured SOPs so your team understands how to operate, maintain, and grow the AI systems in your workflow.
Why work with me?
I hold a degree in Artificial Intelligence Applications and have led National Science and Technology Council (NSTC) research projects. I won a national best innovation award for a sign language recognition system built on smart glasses — combining real-time computer vision with LLM integration on edge hardware.
If you are looking for someone who can both think at the system level and deliver working code, let's talk. Send me a message or click "Invite to Job" — I respond within 24 hours.
Steps for completing your project
After purchasing the project, send requirements so Lawrence can start the project.
Delivery time starts when Lawrence receives requirements from you.
Lawrence works on your project following the steps below.
Revisions may occur after the delivery date.
Dataset Review & Preparation
Evaluate your provided dataset or help define a data collection strategy. Perform preprocessing, augmentation, and labeling if needed.
Model Selection & Architecture Design
Select the most suitable model architecture (e.g., YOLOv8, EfficientDet, ResNet) based on your task, hardware, and performance requirements.