Towards Cross-Domain Single Blood Cell Image Classification Via Large-Scale Lora-Based Segment Anything Model
Author:
Affiliation:
1. Shenzhen Technology University,Shenzhen,China
2. The Third Affiliated Hospital of Sun Yat-sen University,Guangzhou,China
3. South China Normal University,Guangzhou,China
Funder
Research and Development
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10635099/10635102/10635629.pdf?arnumber=10635629
Reference18 articles.
1. An Effective Convolutional Neural Network for Classifying Red Blood Cells in Malaria Diseases
2. A survey on image segmentation of blood and bone marrow smear images with emphasis to automated detection of Leukemia
3. Aggregated Residual Transformations for Deep Neural Networks
4. A new convolutional neural network predictive model for the automatic recognition of hypogranulated neutrophils in myelodysplastic syndromes
5. Unsupervised Cross-Domain Feature Extraction for Single Blood Cell Image Classification
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