AIMC Topic: Deep Learning

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Remote patient monitoring system combining hardware and artificial intelligence based software.

Biomedical physics & engineering express
This study details the development of a remote patient monitoring system with a primary focus on a novel, customized Deep Neural Network (DNN) for arrhythmia detection. The system integrates hardware for real-time data collection from biomedical sens...

Deep learning detection of dynamic exocytosis events in fluorescence TIRF microscopy.

PLoS computational biology
Segmentation and detection of biological objects in fluorescence microscopy is of paramount importance in cell imaging. Deep learning approaches have recently shown promise to advance, automatize and accelerate analysis. However, most of the interest...

Music genre classification with modified residual learning and dual neural network.

PloS one
Music Genre is an abstract property of music that can identify shared traditions and conventions. In the recent past, music genre classification has shown a significant role in MIR that has attracted the research community to draw attention all aroun...

Deep Learning-Assisted Lens-Free Holography Integrated Pd Nanozyme-Armed Phages for the Rapid and Extraction-Free Detection of Viable Bacteria.

Analytical chemistry
Bacterial infections represent a serious global threat to public health, often leading to severe infectious diseases and even fatalities. The most effective approach to prevent outbreaks is through the implementation of rapid, accurate, and simple po...

BCECNN: an explainable deep ensemble architecture for accurate diagnosis of breast cancer.

BMC medical informatics and decision making
BACKGROUND: Breast cancer remains one of the leading causes of cancer-related deaths globally, affecting both women and men. This study aims to develop a novel deep learning (DL)-based architecture, the Breast Cancer Ensemble Convolutional Neural Net...

A mixture of experts (MoE) model to improve AI-based computational pathology prediction performance under variable levels of image blur.

BMC medical imaging
BACKGROUND: AI-based models for analysis of histopathology whole slide images (WSIs) are now common. However, image quality, particularly unsharp areas of WSIs, impacts model performance. In this study we investigate the impact of blur on deep learni...

Robust real-time strawberry maturity detection using UAV-mounted deep learning for precision agriculture.

BMC plant biology
BACKGROUND: To address the challenge of real-time plant monitoring in greenhouse environments, this industry-driven research focuses on developing an autonomous quadrotor UAV system specifically designed for monitoring strawberry plants. Traditional ...

Study on rural landscape design strategies integrating computer vision and deep learning: an analysis based on human perception and visual aesthetics.

Scientific reports
With the increasing application of artificial intelligence in environmental design, computer vision and deep learning have emerged as crucial tools for understanding human visual perception. This study focuses on rural landscapes and proposes a visua...

Streamlined and efficient patient-specific modeling for lumbar spine segmentation and finite element analysis.

Scientific reports
Advancing our understanding of spinal biomechanics through Finite Element Analysis (FEA) is essential for clinical decision-making and biomechanical research. Traditional FEA workflows are hindered by manual segmentation and meshing, introducing inco...

Revolutionizing AMD detection Bi model CNNs and hybrid feature selection for automated grading.

Scientific reports
Age-related macular degeneration (AMD) is a common cause of vision loss in older adults. The automated grading of AMD from fundus images can aid in early detection and treatment. In this research, we propose a comprehensive framework that can enhance...