Computational intelligence and neuroscience
Sep 21, 2022
The development of economy and the needs of urban planning have led to the rapid growth of power applications and the corresponding frequent occurrence of power failures, which many times lead to a series of economic losses due to failure to repair i...
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...
Computational intelligence and neuroscience
Sep 21, 2022
The intelligent reading of English text is affected by complex environmental factors, which will result in low reading accuracy and poor reader experience. Based on the artificial intelligence model, this study constructs the artificial intelligence ...
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...
American journal of industrial medicine
Sep 20, 2022
An algorithm refers to a series of stepwise instructions used by a machine to perform a mathematical operation. In 1955, the term artificial intelligence (AI) was coined to indicate that a machine could be programmed to duplicate human intelligence. ...
Currently, deep learning has been widely applied in the field of object detection, and some relevant scholars have applied it to vehicle detection. In this paper, the deep learning EfficientDet model is analyzed, and the advantages of the model in th...
For permanent magnet DC motors (PMDCMs), the amplitude of the current signals gradually decreases after the motor starts. In this work, the time domain features and time-frequency-domain features extracted from several successive segments of current ...
Social-network-based recommendation algorithms leverage rich social network information to alleviate the problem of data sparsity and boost the recommendation performance. However, traditional social-network-based recommendation algorithms ignore hig...
Among the numerous indoor localization methods, Light-Detection-and-Ranging (LiDAR)-based probabilistic algorithms have been extensively applied to indoor localization due to their real-time performance and high accuracy. Nevertheless, these methods ...
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