AIMC Topic: Machine Learning

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Detection of Benign and Malignant Tumors in Skin Empowered with Transfer Learning.

Computational intelligence and neuroscience
Skin cancer is a major type of cancer with rapidly increasing victims all over the world. It is very much important to detect skin cancer in the early stages. Computer-developed diagnosis systems helped the physicians to diagnose disease, which allow...

Application of Machine Learning in the Reliability Evaluation of Pipelines for the External Anticorrosion Coating.

Computational intelligence and neuroscience
The purpose of this research is to enhance the analysis of the reliability status for external anticorrosive coatings. With the limitation and insufficiency of the static evaluation method, we study and construct an evaluation method of dynamic relia...

Analysis of Sports Video Intelligent Classification Technology Based on Neural Network Algorithm and Transfer Learning.

Computational intelligence and neuroscience
With the rapid development of information technology, digital content shows an explosive growth trend. Sports video classification is of great significance for digital content archiving in the server. Therefore, the accurate classification of sports ...

The past, the present and the future of machine learning and artificial intelligence in anesthesia and Postanesthesia Care Units (PACU).

Minerva anestesiologica
Over the past decade, artificial intelligence (AI) has largely penetrated our daily life. Hence, our expectations regarding clinical AI are very high. However, in healthcare and especially in perioperative medicine, the impact of AI is still relative...

MoËT: Mixture of Expert Trees and its application to verifiable reinforcement learning.

Neural networks : the official journal of the International Neural Network Society
Rapid advancements in deep learning have led to many recent breakthroughs. While deep learning models achieve superior performance, often statistically better than humans, their adoption into safety-critical settings, such as healthcare or self-drivi...

Machine Learning for the Discovery, Design, and Engineering of Materials.

Annual review of chemical and biomolecular engineering
Machine learning (ML) has become a part of the fabric of high-throughput screening and computational discovery of materials. Despite its increasingly central role, challenges remain in fully realizing the promise of ML. This is especially true for th...

Diffusion-weighted MRI radiomics of spine bone tumors: feature stability and machine learning-based classification performance.

La Radiologia medica
PURPOSE: To evaluate stability and machine learning-based classification performance of radiomic features of spine bone tumors using diffusion- and T2-weighted magnetic resonance imaging (MRI).

Using Artificial Intelligence for Assistance Systems to Bring Motor Learning Principles into Real World Motor Tasks.

Sensors (Basel, Switzerland)
Humans learn movements naturally, but it takes a lot of time and training to achieve expert performance in motor skills. In this review, we show how modern technologies can support people in learning new motor skills. First, we introduce important co...

Intelligent Systems Using Sensors and/or Machine Learning to Mitigate Wildlife-Vehicle Collisions: A Review, Challenges, and New Perspectives.

Sensors (Basel, Switzerland)
Worldwide, the persistent trend of human and animal life losses, as well as damage to properties due to wildlife-vehicle collisions (WVCs) remains a significant source of concerns for a broad range of stakeholders. To mitigate their occurrences and i...

The Emotion Probe: On the Universality of Cross-Linguistic and Cross-Gender Speech Emotion Recognition via Machine Learning.

Sensors (Basel, Switzerland)
Machine Learning (ML) algorithms within a human-computer framework are the leading force in speech emotion recognition (SER). However, few studies explore cross-corpora aspects of SER; this work aims to explore the feasibility and characteristics of ...