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Yuta Nakashima

Learning Bottleneck Concepts in Image Classification
Real-time estimation of the remaining surgery duration for cataract surgery using deep convolutional neural networks and long short-term memory
Automated grading system of retinal arterio-venous crossing patterns: A deep learning approach replicating ophthalmologist’s diagnostic process of arteriolosclerosis
Match them up: visually explainable few-shot image classification
Cardiovascular Disease Risk Prediction using Retinal Images via Explainable-AI based models with Traditional CVD risk factor estimation
SCOUTER: Slot Attention-based Classifier for Explainable Image Recognition
Image Retrieval by Hierarchy-aware Deep Hashing Based on Multi-task Learning
MTUNet: Few-shot Image Classification with Visual Explanations
Noisy-LSTM: Improving Temporal Awareness for Video Semantic Segmentation
Match Them Up: Visually Explainable Few-shot Image Classification
Joint Learning of Vessel Segmentation and Artery/Vein Classification with Post-processing
A fully automated grading system for the retinal arteriovenous crossing signs using deep neural network
IterNet: Retinal Image Segmentation Utilizing Structural Redundancy in Vessel Networks