AIMC Topic: Neural Networks, Computer

Clear Filters Showing 15771 to 15780 of 31376 articles

Multi-Sensor Fault Diagnosis of Underwater Thruster Propeller Based on Deep Learning.

Sensors (Basel, Switzerland)
With the rapid development of unmanned surfaces and underwater vehicles, fault diagnoses for underwater thrusters are important to prevent sudden damage, which can cause huge losses. The propeller causes the most common type of thruster damage. Thus,...

3D printed biomimetic cochleae and machine learning co-modelling provides clinical informatics for cochlear implant patients.

Nature communications
Cochlear implants restore hearing in patients with severe to profound deafness by delivering electrical stimuli inside the cochlea. Understanding stimulus current spread, and how it correlates to patient-dependent factors, is hampered by the poor acc...

End-to-end learning for compound activity prediction based on binding pocket information.

BMC bioinformatics
BACKGROUND: Recently, machine learning-based ligand activity prediction methods have been greatly improved. However, if known active compounds of a target protein are unavailable, the machine learning-based method cannot be applied. In such cases, do...

PSCNN: PatchShuffle Convolutional Neural Network for COVID-19 Explainable Diagnosis.

Frontiers in public health
COVID-19 is a sort of infectious disease caused by a new strain of coronavirus. This study aims to develop a more accurate COVID-19 diagnosis system. First, the -conv module (nCM) is introduced. Then we built a 12-layer convolutional neural network...

Image Enhancement Model Based on Deep Learning Applied to the Ureteroscopic Diagnosis of Ureteral Stones during Pregnancy.

Computational and mathematical methods in medicine
OBJECTIVE: To explore the image enhancement model based on deep learning on the effect of ureteroscopy with double J tube placement and drainage on ureteral stones during pregnancy. We compare the clinical effect of ureteroscopy with double J tube pl...

Detecting and grading prostate cancer in radical prostatectomy specimens through deep learning techniques.

Clinics (Sao Paulo, Brazil)
OBJECTIVES: This study aims to evaluate the ability of deep learning algorithms to detect and grade prostate cancer (PCa) in radical prostatectomy specimens.

Application of local fully Convolutional Neural Network combined with YOLO v5 algorithm in small target detection of remote sensing image.

PloS one
This exploration primarily aims to jointly apply the local FCN (fully convolution neural network) and YOLO-v5 (You Only Look Once-v5) to the detection of small targets in remote sensing images. Firstly, the application effects of R-CNN (Region-Convol...

Progressive Diversified Augmentation for General Robustness of DNNs: A Unified Approach.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Adversarial images are imperceptible perturbations to mislead deep neural networks (DNNs), which have attracted great attention in recent years. Although several defense strategies achieved encouraging robustness against adversarial samples, most of ...

Effects of dataset size and interactions on the prediction performance of logistic regression and deep learning models.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Machine learning and deep learning models are very powerful in predicting the presence of a disease. To achieve good predictions, those models require a certain amount of data to train on, whereas this amount i) is generally...

Exploiting dynamic spatio-temporal graph convolutional neural networks for citywide traffic flows prediction.

Neural networks : the official journal of the International Neural Network Society
The prediction of crowd flows is an important urban computing issue whose purpose is to predict the future number of incoming and outgoing people in regions. Measuring the complicated spatial-temporal dependencies with external factors, such as weath...