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Found 6 papers, 5 papers with code
Match Them Up: Visually Explainable Few-shot Image Classification
Few-shot learning (FSL) approaches are usually based on an assumption that the pre-trained knowledge can be obtained from base (seen) categories and can be well transferred to novel (unseen) categories.
Ranked #34 on
Few-Shot Image Classification
on CIFAR-FS 5-way (5-shot)
Automated Grading System of Retinal Arterio-venous Crossing Patterns: A Deep Learning Approach Replicating Ophthalmologist's Diagnostic Process of Arteriolosclerosis
Our severity grading method was able to validate crossing points with precision and recall of 96. 3% and 96. 3%, respectively.
Noisy-LSTM: Improving Temporal Awareness for Video Semantic Segmentation
Semantic video segmentation is a key challenge for various applications.
SCOUTER: Slot Attention-based Classifier for Explainable Image Recognition
Explainable artificial intelligence has been gaining attention in the past few years.
Joint Learning of Vessel Segmentation and Artery/Vein Classification with Post-processing
Retinal imaging serves as a valuable tool for diagnosis of various diseases.
IterNet: Retinal Image Segmentation Utilizing Structural Redundancy in Vessel Networks
Retinal vessel segmentation is of great interest for diagnosis of retinal vascular diseases.
Ranked #5 on
Retinal Vessel Segmentation
on CHASE_DB1
