You will get a Computer Vision model for your application
Project details
You will get a strong computer vision model able to solve tasks like object detection, object tracking, image classification etc.
AI Development Type
Deep Learning, Model TuningAI Tools
Keras, OpenCV, TensorFlowAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$300
|
Standard
$1,500
|
Advanced
$3,000
|
|---|---|---|---|
| Delivery Time | 5 days | 20 days | 60 days |
AI Model Integration | - | - | |
Detailed Code Comments | - | - | |
Knowledge Graph | - | - | - |
Model Documentation | - | - | |
Ontology | - | - | - |
Source Code | - | - | |
Taxonomy | - | - | - |
About Yevhenii
Senior Software Engineer (C++/Python)
Kyiv, Ukraine - 9:52 pm local time
Extensive expertise in C/C++ development, algorithms, and efficient system architecture. Proven experience building cross-platform applications using Qt and working within Linux-based environments, including Yocto for embedded systems.
Experienced AI/ML practitioner, with a particular focus on computer vision. Hands-on experience designing, training, and optimizing deep learning models using Python, TensorFlow, and Keras, including work with modern architectures and real-world datasets.
Strong background in automotive software development, where I served as a team leader on projects such as navigation systems and voice recognition, driving technical direction, mentoring engineers, and ensuring successful delivery.
Skilled in real-time systems, multithreading, and performance optimization, with experience integrating communication protocols like MAVLink and working with robotics frameworks such as ROS.
Proficient with a wide range of tools and technologies including STL, WinAPI, OpenGL/DirectX, SQLite, Protobuf, JSON, MATLAB/Simulink, and version control systems such as Git, SVN, and Gerrit. Experienced in development environments like Visual Studio and Qt Creator, and committed to high code quality through unit testing (Google Test) and engineering best practices.
Steps for completing your project
After purchasing the project, send requirements so Yevhenii can start the project.
Delivery time starts when Yevhenii receives requirements from you.
Yevhenii works on your project following the steps below.
Revisions may occur after the delivery date.
Data overview
The most important step is to understand what data do we have on the table. Is our dataset labeled or not. Does it contain useful features or there is a need to find one. How big the dataset is? Do we need to do any transfer learning to gain perf
Model development
Choose the right model architecture. Choose the proper evaluation protocol. Understanding if the model should be built from scratch or is it possible to reuse another one. Fine tuning of hyper-parameters based on validation metrics.