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Deep transfer learning strategy in intelligent fault diagnosis of rotating machinery
Rotating machinery plays an essential part in many engineering fields. It needs prompt
solutions to the prognosis and health management to ensure the system reliability …
solutions to the prognosis and health management to ensure the system reliability …
[HTML][HTML] A systematic review of few-shot learning in medical imaging
The lack of annotated medical images limits the performance of deep learning models,
which usually need large-scale labelled datasets. Few-shot learning techniques can reduce …
which usually need large-scale labelled datasets. Few-shot learning techniques can reduce …
From characterization to discovery: artificial intelligence, machine learning and high-throughput experiments for heterogeneous catalyst design
This review paper delves into synergistic integration of artificial intelligence (AI) and
machine learning (ML) with high-throughput experimentation (HTE) in the field of …
machine learning (ML) with high-throughput experimentation (HTE) in the field of …
Domain adaptive learning based on equilibrium distribution and dynamic subspace approximation
Nowadays, big data analysis has become an important approach in social information
network. However, the social information may not be distributed independently and …
network. However, the social information may not be distributed independently and …
Trustworthy deep learning framework for the detection of abnormalities in X-ray shoulder images
Musculoskeletal conditions affect an estimated 1.7 billion people worldwide, causing intense
pain and disability. These conditions lead to 30 million emergency room visits yearly, and …
pain and disability. These conditions lead to 30 million emergency room visits yearly, and …
SSP: self-supervised pertaining technique for classification of shoulder implants in x-ray medical images: a broad experimental study
Multiple pathologic conditions can lead to a diseased and symptomatic glenohumeral joint
for which total shoulder arthroplasty (TSA) replacement may be indicated. The long-term …
for which total shoulder arthroplasty (TSA) replacement may be indicated. The long-term …
Machine learning design for high-entropy alloys: models and algorithms
S Liu, C Yang - Metals, 2024 - mdpi.com
High-entropy alloys (HEAs) have attracted worldwide interest due to their excellent
properties and vast compositional space for design. However, obtaining HEAs with low …
properties and vast compositional space for design. However, obtaining HEAs with low …
[HTML][HTML] Opportunities and challenges in the application of large artificial intelligence models in radiology
Influenced by ChatGPT, artificial intelligence (AI) large models have witnessed a global
upsurge in large model research and development. As people enjoy the convenience by this …
upsurge in large model research and development. As people enjoy the convenience by this …
Reducing data requirement for accurate photovoltaic power prediction using hybrid machine learning-physical model on diverse dataset
This research aims to develop a hybrid model combining machine learning and a physical
model and demonstrate its effectiveness across diverse datasets, data scarcity scenarios …
model and demonstrate its effectiveness across diverse datasets, data scarcity scenarios …