Computational intelligence and neuroscience
Sep 21, 2022
Fault diagnosis of rotating machinery is an attractive yet challenging task. This paper presents a novel intelligent fault diagnosis scheme for rotating machinery based on ensemble dilated convolutional neural networks. The novel fault diagnosis fram...
Transfer learning, which involves repurposing a trained model on a related task, may allow for better predictions with substance use data than models that are trained using the target data alone. This approach may also be useful for small clinical da...
Machine learning has been recently used especially in the medical field. In the diagnosis of serious diseases such as cancer, deep learning techniques can be used to reduce the workload of experts and to produce quick solutions. The nuclei found in t...
Background Adrenal masses are common, but radiology reporting and recommendations for management can be variable. Purpose To create a machine learning algorithm to segment adrenal glands on contrast-enhanced CT images and classify glands as normal or...
Neural networks : the official journal of the International Neural Network Society
Sep 20, 2022
In this paper, we study the multi-task sentiment classification problem in the continual learning setting, i.e., a model is sequentially trained to classify the sentiment of reviews of products in a particular category. The use of common sentiment wo...
BACKGROUND /PURPOSE: Establishing an accurate postmortem interval (PMI) is exceptionally crucial in forensic investigation. Artificial intelligence (AI) and Machine learning (ML) models are widely employed in forensic practice. ML is a part of AI, bo...
Biological tissues may be studied using photoacoustic (PA) spectroscopy, which can yield a wealth of physical and chemical data. However, it is really challenging to directly analyse these tissues because of a lot of data. Data mining techniques can ...
Computational intelligence and neuroscience
Sep 20, 2022
In recent years, the increase of customer loan risk and the aggravation of the epidemic have led to the increase of customer default risk. Therefore, identifying high-risk customers has become an important research hotspot for banks. The customer's c...
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