The project focuses on creating a flexible system for medical diagnosis, identifying plant diseases, and general object detection and classification utilizing images, videos, and live data. By employing deep learning, the system delivers precise and prompt outcomes in healthcare, agriculture, and other fields, emphasizing real-time processing for quick choices.

Services Provided:

Deep Learning Expertise:

• Transfer Learning
• YOLO versions 5, 7, 8, 9, and 11
• Multi-model Neural Networks
• Image Processing
• Object Detection
• Image Classification
• Multi-class Classification

Completed Projects Include:

1. A web-based application for real-time skin condition detection using Yolov11.
2. A web-based application for bone fracture detection using Yolov8.
3. Real-time detection of invasive plant species based on CNN.
4. Real-Time Fire and Smoke Detection System.
5. Classification of brain tumors using a transfer learning method.
6. Classification of plant leaf diseases based on the YOLOv9 Model.
7. Classification of citrus leaf diseases using one-shot object detection.
8. Detection and identification of Alzheimer's disease using deep CNNs.

For projects related to medical or plant disease classification and detection, please reach out.

Kindly make contact prior to placing an order