Enhancing Malaria Detection with Tiny Object Detection in Deep Learning
I’ve implemented a CNN-based malaria detection model, but detecting tiny infected red blood cells (RBCs) remains a challenge due to low contrast and scale variations in blood smear images.
To further improve accuracy, I plan to integrate Tiny Object Detection techniques, such as:
🔹 Feature Pyramid Networks (FPN) for better multi-scale feature extraction
🔹 Attention mechanisms to enhance focus on infected RBCs
🔹 Super-resolution methods for improved image clarity
Check out my current implementation on GitHub:
https://github.com/epythonlab2/malaria_detectionLooking forward to exploring more advanced techniques in AI-powered healthcare! Let’s discuss—what are your thoughts? 👇