Human activity recognition utilizing optimized attention induced Multihead Convolutional Neural Network with Mobile Net V1 from Mobile health data

Network Computation in Neural Systems, Год журнала: 2024, Номер unknown, С. 1 - 28

Опубликована: Дек. 17, 2024

Human Activity Recognition (HAR) systems are designed to continuously monitor human behaviour, mainly in the areas of entertainment and surveillance intelligent home environments. In this manuscript, utilizing optimized Attention Induced Multi head Convolutional Neural Network with Mobile Net V1 from Health Data (HAR-AMCNN-MNV1) is proposed. The input data collected through MHEALTH UCI HAR datasets. Spectrospatial Filtering (NSF) used for avoiding accurate labelling reduces errors. Afterwards, Variational Density Peak Clustering Algorithm (VDPCA) segmenting data. Feature Extraction Classification done by (AMCNN-MNV1). AMCNN extracting Hand-crafted features. AMCNN-MNV1 effectively classifies activities as Sitting relaxing (Sit), Climbing stairs (CS), Walking (Walk), Standing still (Std), Waist bends forward (WBF), Frontal elevation arms (FEA), Jogging (Jog), Knees bending (crouching) (KB), Cycling (Cycl), Lying down (Lay), Jump front & back (JFB) Running (Run). Siberian Tiger Optimization (STOA) proposed optimize weight parameter classifier. method attains 21.19%, 23.45%, 21.76% higher accuracy, 31.15%, 24.65% 22.72% precision; 21.15%, 20.18%, 21.28% recall evaluated existing methods.

Язык: Английский

Revolutionizing Microbial Infection Diagnosis: The Role of Artificial Intelligence

Iranian Journal of Medical Microbiology, Год журнала: 2024, Номер 18(2), С. 66 - 79

Опубликована: Май 25, 2024

Artificial intelligence (AI), described as computer algorithms that exhibit cognitive characteristics like learning abilities, now affecting our lives in many areas.In the medical field, AI-supported image analysis has already taken on a central role pathology, radiology and dermatology.The policy of this review consisted peer-reviewed literature annotated Web Science, Scopus, PubMed Google Scholar databases.Articles were reviewed describe use AI to analyze images diagnose infectious diseases.Digitization healthcare is having profound impact patients.It expected development started will continue gain momentum.Machine fundamentally changing way we interact with health-related data, including clinical microbiology disease data.We likely transition from Internet Things environment Bodies devices providing detailed health data even disease-free times.The focus study was current views attempts apply methods daily practice, well search for promising diseases most efficient way.

Язык: Английский