Abstract: In this work, we demonstrate a compressed time-domain, pooling-aware convolution (COMPAC) convolutional neural network (CNN) engine for energy-efficient edge AI computing by performing multi ...
A gentle introduction to video technology, although it's aimed at software developers / engineers, we want to make it easy for anyone to learn. This idea was born during a mini workshop for newcomers ...
Speaker diarization, identifying “who spoke when,” plays a vital role in speech transcription, supervised fine-tuning of large language models, conversational AI, and audio content analysis by ...
Speech disorder detection (SDD) models can assist speech therapists in providing personalized treatment to individuals with speech impairment. Speech disorders (SDs) comprise a broad spectrum of ...
Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to ...
Recently, seismic inversion has made extensive use of supervised learning methods. The traditional deep learning inversion network can utilize the temporal correlation in the vertical direction. Still ...
Abstract: Recent deep neural network (DNN) based single-channel speech enhancement methods have achieved remarkable results in the time-frequency (TF) magnitude domain. To further improve the quality ...
In terms of seizure prediction, how to fully mine relational data information among multiple channels of epileptic EEG? This is a scientific research subject worthy of further exploration. Recently, ...
DNA N6-methylation (6mA) in Adenine nucleotide is a post replication modification responsible for many biological functions. Automated and accurate computational methods can help to identify 6mA sites ...
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