AIMC Topic: Deep Learning

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Variational mode decomposition combined fuzzy-Twin support vector machine model with deep learning for solar photovoltaic power forecasting.

PloS one
A novel Variational Mode Decomposition (VMD) combined Fuzzy-Twin Support Vector Machine Model with deep learning mechanism is devised in this research study to forecast the solar Photovoltaic (PV) output power in day ahead basis. The raw data from th...

Usefulness of deep learning-based noise reduction for 1.5 T MRI brain images.

Clinical radiology
AIM: To evaluate 1.5 T magnetic resonance imaging (MRI) brain images with denoising procedures using deep learning-based reconstruction (dDLR) relative to the original 1.5 and 3 T images.

Vessel and tissue recognition during third-space endoscopy using a deep learning algorithm.

Gut
In this study, we aimed to develop an artificial intelligence clinical decision support solution to mitigate operator-dependent limitations during complex endoscopic procedures such as endoscopic submucosal dissection and peroral endoscopic myotomy, ...

Super-resolution of brain tumor MRI images based on deep learning.

Journal of applied clinical medical physics
INTRODUCTION: To explore and evaluate the performance of MRI-based brain tumor super-resolution generative adversarial network (MRBT-SR-GAN) for improving the MRI image resolution in brain tumors.

Robust deep learning-based protein sequence design using ProteinMPNN.

Science (New York, N.Y.)
Although deep learning has revolutionized protein structure prediction, almost all experimentally characterized de novo protein designs have been generated using physically based approaches such as Rosetta. Here, we describe a deep learning-based pro...

Hallucinating symmetric protein assemblies.

Science (New York, N.Y.)
Deep learning generative approaches provide an opportunity to broadly explore protein structure space beyond the sequences and structures of natural proteins. Here, we use deep network hallucination to generate a wide range of symmetric protein homo-...

Deep Ensemble Fake News Detection Model Using Sequential Deep Learning Technique.

Sensors (Basel, Switzerland)
Recently, fake news has been widely spread through the Internet due to the increased use of social media for communication. Fake news has become a significant concern due to its harmful impact on individual attitudes and the community's behavior. Res...

Direct mapping from PET coincidence data to proton-dose and positron activity using a deep learning approach.

Physics in medicine and biology
. Obtaining the intrinsic dose distributions in particle therapy is a challenging problem that needs to be addressed by imaging algorithms to take advantage of secondary particle detectors. In this work, we investigate the utility of deep learning me...

COVID-19 Semantic Pneumonia Segmentation and Classification Using Artificial Intelligence.

Contrast media & molecular imaging
Coronavirus 2019 (COVID-19) has become a pandemic. The seriousness of COVID-19 can be realized from the number of victims worldwide and large number of deaths. This paper presents an efficient deep semantic segmentation network (DeepLabv3Plus). Initi...

Evaluation Method of Public Physical Training Quality Based on Global Topology Optimization Deep Learning Model.

Journal of environmental and public health
In the quality evaluation of public sports training, the selected indicators are not comprehensive, resulting in some errors in the results of quality evaluation. Therefore, this paper designs a public sports training quality evaluation method based ...