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Found 5 papers, 1 papers with code
ICIP 2022 Challenge on Parasitic Egg Detection and Classification in Microscopic Images: Dataset, Methods and Results
Manual examination of faecal smear samples to identify the existence of parasitic eggs is very time-consuming and can only be done by specialists.
Detection of Parasitic Eggs from Microscopy Images and the emergence of a new dataset
Automatic detection of parasitic eggs in microscopy images has the potential to increase the efficiency of human experts whilst also providing an objective assessment.
Parasitic Egg Detection and Classification in Low-cost Microscopic Images using Transfer Learning
The traditional diagnosis usually relies on manual analysis from microscopic images which is prone to human error due to morphological similarity of different parasitic eggs and abundance of impurities in a sample.
Analysis of Vision-based Abnormal Red Blood Cell Classification
This paper presents an automated process utilising the advantages of machine learning to increase capacity and standardisation of cell abnormality detection, and its performance is analysed.
Red Blood Cell Segmentation with Overlapping Cell Separation and Classification on Imbalanced Dataset
The imbalance ratio of this dataset was 34. 538 for 12 RBC classes from 20, 875 individual RBC samples.
