AIMC Topic: Neural Networks, Computer

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Optimization of the Mixed Gas Detection Method Based on Neural Network Algorithm.

ACS sensors
Real-time mixed gas detection has attracted significant interest for being a key factor for applications of the electronic nose (E-nose). However, mixed gas detection still faces the challenge of long detection time and a large amount of training dat...

BERT for Activity Recognition Using Sequences of Skeleton Features and Data Augmentation with GAN.

Sensors (Basel, Switzerland)
Recently, the scientific community has placed great emphasis on the recognition of human activity, especially in the area of health and care for the elderly. There are already practical applications of activity recognition and unusual conditions that...

Human-Computer Interaction with a Real-Time Speech Emotion Recognition with Ensembling Techniques 1D Convolution Neural Network and Attention.

Sensors (Basel, Switzerland)
Emotions have a crucial function in the mental existence of humans. They are vital for identifying a person's behaviour and mental condition. Speech Emotion Recognition (SER) is extracting a speaker's emotional state from their speech signal. SER is ...

A Survey on Low-Latency DNN-Based Speech Enhancement.

Sensors (Basel, Switzerland)
This paper presents recent advances in low-latency, single-channel, deep neural network-based speech enhancement systems. The sources of latency and their acceptable values in different applications are described. This is followed by an analysis of t...

A Tiny Matched Filter-Based CNN for Inter-Patient ECG Classification and Arrhythmia Detection at the Edge.

Sensors (Basel, Switzerland)
Automated electrocardiogram (ECG) classification using machine learning (ML) is extensively utilized for arrhythmia detection. Contemporary ML algorithms are typically deployed on the cloud, which may not always meet the availability and privacy requ...

An intelligent medical guidance and recommendation model driven by patient-physician communication data.

Frontiers in public health
Based on the online patient-physician communication data, this study used natural language processing and machine learning algorithm to construct a medical intelligent guidance and recommendation model. First, based on 16,935 patient main complaint d...

MaskID: An effective deep-learning-based algorithm for dense rebar counting.

PloS one
As a dense instance segmentation problem, rebar counting in a complex environment such as rebar yard and rebar transpotation has received significant attention in both academic and industrial contexts. Traditional counting approaches, such as manual ...

Early recognition of risk of critical adverse events based on deep neural decision gradient boosting.

Frontiers in public health
INTRODUCTION: Perioperative critical events will affect the quality of medical services and threaten the safety of patients. Using scientific methods to evaluate the perioperative risk of critical illness is of great significance for improving the qu...

Improved neural network for predicting blood donations based on two emergent factors.

Transfusion clinique et biologique : journal de la Societe francaise de transfusion sanguine
BACKGROUND: Blood donation forecasting is a critical part of blood supply chain management. However, few studies have focused on modeling blood donation with different emergency factors. The purpose of this study was to investigate the effects of dif...

Deep neural network architecture for automated soft surgical skills evaluation using objective structured assessment of technical skills criteria.

International journal of computer assisted radiology and surgery
PURPOSE: Classic methods of surgery skills evaluation tend to classify the surgeon performance in multi-categorical discrete classes. If this classification scheme has proven to be effective, it does not provide in-between evaluation levels. If these...