AIMC Topic: Neural Networks, Computer

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MRM-BERT: a novel deep neural network predictor of multiple RNA modifications by fusing BERT representation and sequence features.

RNA biology
RNA modifications play crucial roles in various biological processes and diseases. Accurate prediction of RNA modification sites is essential for understanding their functions. In this study, we propose a hybrid approach that fuses a pre-trained sequ...

A Q-transform-based deep learning model for the classification of atrial fibrillation types.

Physical and engineering sciences in medicine
According to the World Health Organization (WHO), Atrial Fibrillation (AF) is emerging as a global epidemic, which has resulted in a need for techniques to accurately diagnose AF and its various subtypes. While the classification of cardiac arrhythmi...

TFCNet: A texture-aware and fine-grained feature compensated polyp detection network.

Computers in biology and medicine
PURPOSE: Abnormal tissue detection is a prerequisite for medical image analysis and computer-aided diagnosis and treatment. The use of neural networks (CNN) to achieve accurate detection of intestinal polyps is beneficial to the early diagnosis and t...

Innovative approach for predicting daily reference evapotranspiration using improved shallow and deep learning models in a coastal region: A comparative study.

Journal of environmental management
Accurate and reliable estimation of Reference Evapotranspiration (ETo) is crucial for water resources management, hydrological processes, and agricultural production. The FAO-56 Penman-Monteith (FAO-56PM) approach is recommended as the standard model...

Enhancing speaker identification through reverberation modeling and cancelable techniques using ANNs.

PloS one
This paper introduces a method aiming at enhancing the efficacy of speaker identification systems within challenging acoustic environments characterized by noise and reverberation. The methodology encompasses the utilization of diverse feature extrac...

Using spatio-temporal graph neural networks to estimate fleet-wide photovoltaic performance degradation patterns.

PloS one
Accurate estimation of photovoltaic (PV) system performance is crucial for determining its feasibility as a power generation technology and financial asset. PV-based energy solutions offer a viable alternative to traditional energy resources due to t...

Accurate Liver Fibrosis Detection Through Hybrid MRMR-BiLSTM-CNN Architecture with Histogram Equalization and Optimization.

Journal of imaging informatics in medicine
The early detection and accurate diagnosis of liver fibrosis, a progressive and potentially serious liver condition, are crucial for effective medical intervention. Invasive methods like biopsies for diagnosis can be risky and expensive. This researc...

Efficient leukocytes detection and classification in microscopic blood images using convolutional neural network coupled with a dual attention network.

Computers in biology and medicine
Leukocytes, also called White Blood Cells (WBCs) or leucocytes, are the cells that play a pivotal role in human health and are vital indicators of diseases such as malaria, leukemia, AIDS, and other viral infections. WBCs detection and classification...

A Spiking Artificial Vision Architecture Based on Fully Emulating the Human Vision.

Advanced materials (Deerfield Beach, Fla.)
Intelligent vision necessitates the deployment of detectors that are always-on and low-power, mirroring the continuous and uninterrupted responsiveness characteristic of human vision. Nonetheless, contemporary artificial vision systems attain this go...

Deep learning segmentation of peri-sinus structures from structural magnetic resonance imaging: validation and normative ranges across the adult lifespan.

Fluids and barriers of the CNS
BACKGROUND: Peri-sinus structures such as arachnoid granulations (AG) and the parasagittal dural (PSD) space have gained much recent attention as sites of cerebral spinal fluid (CSF) egress and neuroimmune surveillance. Neurofluid circulation dysfunc...