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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Aided Diagnosis of?Autism Spectrum Disorder Based on?a?Mixed Neural Network Model the conventional methods are questionnaires and behavioral observation, which may be subjective and cause misdiagnosis. In order to obtain an accurate diagnosis, we could explore the quantitative imaging biomarkers and leverage the machine learning to learn the classification model on these biomark

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Multi-scale Feature Fusion Neural Network for?Accurate Prediction of?Drug-Target Interactionsng process that involves conducting biological experiments with a vast array of potential compounds. To accelerate this process, computational methods have been developed, and with the growth of available datasets, deep learning methods have been widely applied in this field. Despite the emergence o

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GoatPose: A Lightweight and?Efficient Network with?Attention Mechanismlutional networks to edge devices. In this paper, we present GoatPose: a lightweight deep convolutional model for real-time human keypoint detection incorporating attention mechanism. Since the high computational cost is associated with the frequently-use convolution block, we substitute it with our

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Sign Language Recognition for?Low Resource Languages Using Few Shot Learnings crucial to leverage a few-shot learning strategy for SLR. This research proposes a novel skeleton-based sign language recognition method based on the prototypical network?[.] called ProtoSign. Furthermore, we contribute to the field by introducing the first publicly accessible dynamic word-level S