Titlebook: Neural Information Processing; 30th International C Biao Luo,Long Cheng,Chaojie Li Conference proceedings 2024 The Editor(s) (if applicable

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neoplasm

Biological Tissue Sections Instance Segmentation Based on Active Learningignificant value as the training set, so we can only label a small number of samples, and the network can achieve the expected performance. The algorithm is robust to different shapes of tissue sections and can be applied to various complex scenes to segment tissue sections automatically. Furthermor

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gastritis

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myopia

EEG Epileptic Seizure Classification Using Hybrid Time-Frequency Attention Deep Networke time-frequency features which provides seizure relevant information within the EEG signals. Then, a hybrid deep network combining convolutional neural network (CNN) and bidirectional LSTM (BiLSTM) architecture extracts spatiotemporal dependencies of EEG signals. Experimental studies have been perf

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LDW-RS Loss: Label Density-Weighted Loss with Ranking Similarity Regularization for Imbalanced Deep designed to capture information about the similarity between neighboring samples in the label space. Ranking similarity regularization is developed to establish a global constraint for calibrating the biased feature representations learned by the network. A total of 1327 MRI images from 157 healthy