AIMC Topic: Machine Learning

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Parallax attention stereo matching network based on the improved group-wise correlation stereo network.

PloS one
Recent stereo matching methods, especially end-to-end deep stereo matching networks, have achieved remarkable performance in the fields of autonomous driving and depth sensing. However, state-of-the-art stereo algorithms, even with the deep neural ne...

Scalp EEG-Based Pain Detection Using Convolutional Neural Network.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Pain is an integrative phenomenon coupled with dynamic interactions between sensory and contextual processes in the brain, often associated with detectable neurophysiological changes. Recent advances in brain activity recording tools and machine lear...

Machine Learning at the Interface of Polymer Science and Biology: How Far Can We Go?

Biomacromolecules
This Perspective outlines recent progress and future directions for using machine learning (ML), a data-driven method, to address critical questions in the design, synthesis, processing, and characterization of . The achievement of these tasks requir...

A Concise Review on Recent Developments of Machine Learning for the Prediction of Vibrational Spectra.

The journal of physical chemistry. A
Machine learning has become more and more popular in computational chemistry, as well as in the important field of spectroscopy. In this concise review, we walk the reader through a short summary of machine learning algorithms and a comprehensive dis...

PhageLeads: Rapid Assessment of Phage Therapeutic Suitability Using an Ensemble Machine Learning Approach.

Viruses
The characterization of therapeutic phage genomes plays a crucial role in the success rate of phage therapies. There are three checkpoints that need to be examined for the selection of phage candidates, namely, the presence of temperate markers, anti...

Application of Knowledge Distillation Based on Transfer Learning of ERNIE Model in Intelligent Dialogue Intention Recognition.

Sensors (Basel, Switzerland)
The 'intention' classification of a user question is an important element of a task-engine driven chatbot. The essence of a user question's intention understanding is the text classification. The transfer learning, such as BERT (Bidirectional Encoder...

Machine learning outperforms clinical experts in classification of hip fractures.

Scientific reports
Hip fractures are a major cause of morbidity and mortality in the elderly, and incur high health and social care costs. Given projected population ageing, the number of incident hip fractures is predicted to increase globally. As fracture classificat...

Vehicle Image Detection Method Using Deep Learning in UAV Video.

Computational intelligence and neuroscience
Traditional machine learning algorithms are susceptible to objective factors such as video quality and weather environment in the vehicle detection of Unmanned Aerial Vehicle (UAV) videos, resulting in poor detection results. A vehicle image detectio...

Analyzing the Effect of Vaccination Over COVID Cases and Deaths in Asian Countries Using Machine Learning Models.

Frontiers in cellular and infection microbiology
Coronavirus Disease 2019 (COVID-19) is spreading across the world, and vaccinations are running parallel. Coronavirus has mutated into a triple-mutated virus, rendering it deadlier than before. It spreads quickly from person to person by contact and ...

Framework for Integrating Equity Into Machine Learning Models: A Case Study.

Chest
Predictive analytic models leveraging machine learning methods increasingly have become vital to health care organizations hoping to improve clinical outcomes and the efficiency of care delivery for all patients. Unfortunately, predictive models coul...