Coffee Bean Defects Automatic Classification Realtime Application Adopting Deep Learning

5,500.00
Aim: The aim of this project is to propose an efficient, real-time system for automatic classification of coffee bean defects using the YOLOv8 deep learning model.

Deep Learning Technique to detect Brain tumor disease using YOLOv8

5,500.00
Aim: The aim of this research is to develop a more effective and efficient brain tumor segmentation system using the YOLOv8 architecture.

Enhancing Road Safety: Detection of Animals on Highways During Night

5,500.00

Aim:

Ā  Ā  Ā  Ā  Design and deploy a real-time, low-light-robust animal detection system using YOLOv8 for highways that reliably identifies animals at night and triggers timely driver/road-side alerts to reduce collisions.

Lung Nodule Detection in Medical Images Based on Improved YOLOv5

5,500.00
Aim: To enhance the YOLOv8 model for achieving high-performance object detection in medical imaging and other specialized applications.