AIMC Topic: Neural Networks, Computer

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Prediction of hydrophilic and hydrophobic hydration structure of protein by neural network optimized using experimental data.

Scientific reports
The hydration structures of proteins, which are necessary for their folding, stability, and functions, were visualized using X-ray and neutron crystallography and transmission electron microscopy. However, complete visualization of hydration structur...

A deep learning model for detection of leukocytes under various interference factors.

Scientific reports
The accurate detection of leukocytes is the basis for the diagnosis of blood system diseases. However, diagnosing leukocyte disorders by doctors is time-consuming and requires extensive experience. Automated detection methods with high accuracy can i...

Fault-Level Grading of Photovoltaic Cells Employing Lightweight Deep Learning Models.

Computational intelligence and neuroscience
The deployment of photovoltaic (PV) cells as a renewable energy resource has been boosted recently, which enhanced the need to develop an automatic and swift fault detection system for PV cells. Prior to isolation for repair or replacement, it is cri...

Forecasting the United State Dollar(USD)/Bangladeshi Taka (BDT) exchange rate with deep learning models: Inclusion of macroeconomic factors influencing the currency exchange rates.

PloS one
Forecasting a currency exchange rate is one of the most challenging tasks nowadays. Due to government monetary policy and some uncertain factors, such as political stability, it becomes difficult to correctly forecast the currency exchange rate. Prev...

Automating the Standardized Cosmesis and Health Nasal Outcomes Survey Classification with Convolutional Neural Networks.

Facial plastic surgery & aesthetic medicine
Currently, the aesthetic appearance and structure of the nose in a rhinoplasty patient is evaluated by a surgeon, without automation. To compare the assessment of convolutional neural networks (CNNs) (machine learning) and a rhinoplasty surgeon's i...

Spatiotemporal analysis of speckle dynamics to track invisible needle in ultrasound sequences using convolutional neural networks: a phantom study.

International journal of computer assisted radiology and surgery
PURPOSE: Accurate needle placement into the target point is critical for ultrasound interventions like biopsies and epidural injections. However, aligning the needle to the thin plane of the transducer is a challenging issue as it leads to the decay ...

SuperFormer: Continual learning superposition method for text classification.

Neural networks : the official journal of the International Neural Network Society
One of the biggest challenges in continual learning domains is the tendency of machine learning models to forget previously learned information over time. While overcoming this issue, the existing approaches often exploit large amounts of additional ...

Searching by parts: Towards fine-grained image retrieval respecting species correlation.

Gene expression patterns : GEP
Most of the existing works on fine-grained image categorization and retrieval focus on finding similar images from the same species and often give little importance to inter-species similarities. However, these similarities may carry species correlat...

Deep compressed sensing MRI via a gradient-enhanced fusion model.

Medical physics
BACKGROUND: Compressed sensing has been employed to accelerate magnetic resonance imaging by sampling fewer measurements. However, conventional iterative optimization-based CS-MRI are time-consuming for iterative calculations and often share poor gen...

Artificial Neural Network-Assisted Classification of Hearing Prognosis of Sudden Sensorineural Hearing Loss With Vertigo.

IEEE journal of translational engineering in health and medicine
This study aimed to determine the impact on hearing prognosis of the coherent frequency with high magnitude-squared wavelet coherence (MSWC) in video head impulse test (vHIT) among patients with sudden sensorineural hearing loss with vertigo (SSNHLV)...