mahmudulalam/complete-blood-cell-count-dataset

The complete blood count (CBC) dataset contains a total of 360 blood smear images of red blood cells (RBCs), white blood cells (WBCs), and Platelets with annotations.

I am Mohammad Mahmudul Alam, Ph.D. candidate in Computer Science at UMBC. My ongoing research involves neuro-symbolic representations and their applications to deep learning. Currently, I am working as a Graduate Research Assistant in the CORAL lab at UMBC where I am advised by Professor Dr. Tim Oates and co-advised by Dr. Edward Raff.

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complete-blood-cell-count-dataset's Issues

Asking for an advise

Hello! Thank you for your great work. I have a few questions.

I am trying to train a model with dental panoramic radiographs. I have similar number of dataset as you did. However, I have much smaller number of labels. It means that I have about 1000 datasets with about 1-3 labels in each image. I am wondering if this is why I keep getting decreasing training error with increasing validation error due to an overfitting. I know that I do not have enough samples and overfitting occurs naturally but it happens too early. Also, training and validation sets are too different in performance.

Would I be able to know your cfg settings? Have you had this kind of problem? Would you give me an advise if you did? We have used yolov4 in darknet and had the same problem using tiny. Please give us some advice if you could.

Thank you for reading this comment and I hope you have a great day!

How are you annotating the images?

Could you provide a useful way to annotate images. I'd like to use your program but need to figure out the annotation method first. If you could provide that information it would be very useful.