Tune YOLO v3 architecture for object detection
$30-250 USD
Paiement à la livraison
As part of a larger system we need to detect and count small objects in close proximity using machine vision. We are having partial success using the YOLO v3 deep learning framework but need help to configure the architecture and tune the parameters to improve performance. We have datasets, test images, etc, and can provide all that to you. We're using Python and OpenCV. You need to be familiar with YOLO and able to advise us to adjust things like anchor boxes, grid size, etc, and understand its impact on detection performance.
Nº du projet : #17903258
À propos du projet
Décerné à:
Hi. My name is Uzair.I did my masters in Electrical Engineering. I have done my thesis in biomedical signal processing and Machine learning. I have more than 3 years of experience in Python/MATLAB specially in Machin Plus
6 freelances font une offre moyenne de 182 $ pour ce travail
Hello! I am a python developer. I looked at your project and it seems interesting. I have all necessary skills required for this project. Ping me to discuss in detail.
Hello I have read the requirements of your project with very carefully and i am interested I have rich experience of developing web and mobile app developments If you give me opportunity, I will do my best for Plus
I have already done one project in machine learning and deep learning car logo recognition. Give me a chance I will give my better .
