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Found 5 papers, 1 papers with code
Computer-Aided Cytology Diagnosis in Animals: CNN-Based Image Quality Assessment for Accurate Disease Classification
The research sheds light on the significance of CNN-based IQA in computer-aided cytology diagnosis for animals, enhancing the accuracy of disease classification.
Using simulation to calibrate real data acquisition in veterinary medicine
This paper explores the innovative use of simulation environments to enhance data acquisition and diagnostics in veterinary medicine, focusing specifically on gait analysis in dogs.
Assessing Dataset Quality Through Decision Tree Characteristics in Autoencoder-Processed Spaces
In this paper, we delve into the critical aspect of dataset quality assessment in machine learning classification tasks.
Using super-resolution for enhancing visual perception and segmentation performance in veterinary cytology
The primary objective of this research was to enhance the quality of semantic segmentation in cytology images by incorporating super-resolution (SR) architectures.
Segmentation of the veterinary cytological images for fast neoplastic tumors diagnosis
This paper shows the machine learning system which performs instance segmentation of cytological images in veterinary medicine.
