This article describes a multimodal fusion data acquisition and processing system about electromyography for dynamic movement recognition and bioelectrical impedance for key posture recognition. In addition, a new dynamic–static fusion algorithm strategy is designed.
Chenhao Cao +5 more
wiley +1 more source
Comparative evaluation of deep learning models for cardiovascular disease diagnosis and classification. [PDF]
Bhia I, Soltanizadeh S, Shafik W.
europepmc +1 more source
The use of image quality metrics in combination with machine learning enables automatic image quality assessment for fluorescence microscopy images. The method can be integrated into the experimental pipeline for optical microscopy and utilized to classify artifacts in experimental images and to build quality rankings with a reference‐free approach ...
Elena Corbetta, Thomas Bocklitz
wiley +1 more source
Precision cotton disease detection via transformer models applied to leaf imagery. [PDF]
Inamdar N +5 more
europepmc +1 more source
A Hybrid Transfer Learning Framework for Brain Tumor Diagnosis
A novel hybrid transfer learning approach for brain tumor classification achieves 99.47% accuracy using magnetic resonance imaging (MRI) images. By combining image preprocessing, ensemble deep learning, and explainable artificial intelligence (XAI) techniques like gradient‐weighted class activation mapping and SHapley Additive exPlanations (SHAP), the ...
Sadia Islam Tonni +11 more
wiley +1 more source
Development and evaluation of an artificial intelligence-based electrocardiogram prediction model for emergency chest pain patients. [PDF]
Luo Y +5 more
europepmc +1 more source
Haptic In‐Sensor Computing Device Based on CNT/PDMS Nanocomposite Physical Reservoir
Using a porous carbon nanotube‐polydimethylsiloxane nanocomposite, a sensor array integrated with a physical reservoir computing paradigm capable of in‐sensor computing is demonstrated. The device is able to classify between nine objects with an accuracy above 80%, opening the possibility for low‐power sensing/computing for future robotics.
Kouki Kimizuka +7 more
wiley +1 more source
Deep locomotion prediction learning over biosensors, ambient sensors, and computer vision. [PDF]
Javeed M, Jalal A, AlHammadi DA, Lee B.
europepmc +1 more source
Perceiving Physiology from the Voice: Evidence for Physiological Coupling Between Laryngeal and Epilaryngeal Adjustments. [PDF]
Zhang Z, Steinhauer K.
europepmc +1 more source
Erratum: Neural extracellular matrix regulates visual sensory motor integration. [PDF]
Reinhard J +11 more
europepmc +1 more source

