AIMC Topic: Machine Learning

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Towards Robustifying Image Classifiers against the Perils of Adversarial Attacks on Artificial Intelligence Systems.

Sensors (Basel, Switzerland)
Adversarial machine learning (AML) is a class of data manipulation techniques that cause alterations in the behavior of artificial intelligence (AI) systems while going unnoticed by humans. These alterations can cause serious vulnerabilities to missi...

Characterization of Biocomposites and Glass Fiber Epoxy Composites Based on Acoustic Emission Signals, Deep Feature Extraction, and Machine Learning.

Sensors (Basel, Switzerland)
This study presents the results of acoustic emission (AE) measurements and characterization in the loading of biocomposites at room and low temperatures that can be observed in the aviation industry. The fiber optic sensors (FOS) that can outperform ...

Comments on "Identifying psychological antecedents and predictors of vaccine hesitancy through machine learning: A cross sectional study among chronic disease patients of deprived urban neighbourhood, India".

Monaldi archives for chest disease = Archivio Monaldi per le malattie del torace
Dear Editor, we read the publication by Rustagi et al. "Identifying psychological antecedents and predictors of vaccine hesitancy through machine learning: A cross sectional study among chronic disease patients of deprived urban neighbourhood, India"...

An investigation of privacy preservation in deep learning-based eye-tracking.

Biomedical engineering online
BACKGROUND: The expanding usage of complex machine learning methods such as deep learning has led to an explosion in human activity recognition, particularly applied to health. However, complex models which handle private and sometimes protected data...

A Fast Decision Algorithm for VVC Intra-Coding Based on Texture Feature and Machine Learning.

Computational intelligence and neuroscience
Due to the development and application of information technology, a series of modern information technologies represented by 5G, big data, and artificial intelligence are changing rapidly, and people's requirements for video coding standards have bec...

Artificial intelligence for oral cancer diagnosis: What are the possibilities?

Oral oncology
Oral cancer could be prevented. The primary strategy is based on prevention. Most patients with oral cancer present to the hospital network with advanced staging and a low chance of cure. This condition may be related to physicians' difficulty of mak...

Nucleophilicity Prediction Using Graph Neural Networks.

Journal of chemical information and modeling
The quantitative description between chemical reaction rates and nucleophilicity parameters plays a crucial role in organic chemistry. In this regard, the formula proposed by Mayr et al. and the constructed reactivity database are important represent...

Lifelong Adaptive Machine Learning for Sensor-Based Human Activity Recognition Using Prototypical Networks.

Sensors (Basel, Switzerland)
Continual learning (CL), also known as lifelong learning, is an emerging research topic that has been attracting increasing interest in the field of machine learning. With human activity recognition (HAR) playing a key role in enabling numerous real-...

Ensemble stacking rockburst prediction model based on Yeo-Johnson, K-means SMOTE, and optimal rockburst feature dimension determination.

Scientific reports
Rockburst forecasting plays a crucial role in prevention and control of rockburst disaster. To improve the accuracy of rockburst prediction at the data structure and algorithm levels, the Yeo-Johnson transform, K-means SMOTE oversampling, and optimal...