AIMC Topic: Neural Networks, Computer

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Machine Learning of Reaction Properties via Learned Representations of the Condensed Graph of Reaction.

Journal of chemical information and modeling
The estimation of chemical reaction properties such as activation energies, rates, or yields is a central topic of computational chemistry. In contrast to molecular properties, where machine learning approaches such as graph convolutional neural netw...

Developing an iOS application that uses machine learning for the automated diagnosis of blepharoptosis.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
PURPOSE: To assess the performance of artificial intelligence in the automated classification of images taken with a tablet device of patients with blepharoptosis and subjects with normal eyelid.

Assembled graph neural network using graph transformer with edges for protein model quality assessment.

Journal of molecular graphics & modelling
Acquainting protein's structure is of vital importance to accurately understanding its function. Computational method of deep learning has made great progress in protein structure prediction from sequence, and has the potential to help structural bio...

Autonomous Thermal Vision Robotic System for Victims Recognition in Search and Rescue Missions.

Sensors (Basel, Switzerland)
Technological breakthroughs in recent years have led to a revolution in fields such as Machine Vision and Search and Rescue Robotics (SAR), thanks to the application and development of new and improved neural networks to vision models together with m...

Time Series Segmentation Based on Stationarity Analysis to Improve New Samples Prediction.

Sensors (Basel, Switzerland)
A wide range of applications based on sequential data, named time series, have become increasingly popular in recent years, mainly those based on the Internet of Things (IoT). Several different machine learning algorithms exploit the patterns extract...

A novel Joint-Net model for recognizing small-bowel polyp images.

Minimally invasive therapy & allied technologies : MITAT : official journal of the Society for Minimally Invasive Therapy
INTRODUCTION: To automatically recognize polyps of enteroscopy images and avoid pathological change, a novel Joint-Net has been proposed.

A multiscale double-branch residual attention network for anatomical-functional medical image fusion.

Computers in biology and medicine
Medical image fusion technology synthesizes complementary information from multimodal medical images. This technology is playing an increasingly important role in clinical applications. In this paper, we propose a new convolutional neural network, wh...

Ms RED: A novel multi-scale residual encoding and decoding network for skin lesion segmentation.

Medical image analysis
Computer-Aided Diagnosis (CAD) for dermatological diseases offers one of the most notable showcases where deep learning technologies display their impressive performance in acquiring and surpassing human experts. In such the CAD process, a critical s...

Minimum spanning tree based graph neural network for emotion classification using EEG.

Neural networks : the official journal of the International Neural Network Society
Emotion classification based on neurophysiology signals has been a challenging issue in the literature. Recent neuroscience findings suggest that brain network structure underlying the different emotions provides a window in understanding human affec...

On Connections Between Regularizations for Improving DNN Robustness.

IEEE transactions on pattern analysis and machine intelligence
This paper analyzes regularization terms proposed recently for improving the adversarial robustness of deep neural networks (DNNs), from a theoretical point of view. Specifically, we study possible connections between several effective methods, inclu...