As the number of people suffering from cardiovascular diseases increases every year, it becomes essential to have an accurate automatic electrocardiogram (ECG) diagnosis system. Researchers have adopted different methods, such as deep learning, to in...
A channel modeling method and deep-learning-based symbol decision method are proposed to improve the performance of a visual MIMO system for communication between a variable-color LED array and camera. Although image processing algorithms using color...
Label noise is omnipresent in the annotations process and has an impact on supervised learning algorithms. This work focuses on the impact of label noise on the performance of learning models by examining the effect of random and class-dependent labe...
Exchanging gradient is a widely used method in modern multinode machine learning system (e.g., distributed training, Federated Learning). Gradients and weights of model has been presumed to be safe to delivery. However, some studies have shown that g...
BACKGROUND: In disease areas with 'soft' outcomes (i.e., the subjective aspects of a medical condition or its management) such as migraine or depression, extraction and validation of real-world evidence (RWE) from electronic health records (EHRs) and...
Individual daily travel activities (e.g., work, eating) are identified with various machine learning models (e.g., Bayesian Network, Random Forest) for understanding people's frequent travel purposes. However, labor-intensive engineering work is ofte...
PURPOSE: To apply deep learning (DL) techniques to develop an automatic intelligent classification system identifying the specific types of myopic maculopathy (MM) based on macular optical coherence tomography (OCT) images using transfer learning (TL...
Balance impairment (BI) is an important cause of falls in the elderly. However, the existing balance estimation system needs to measure a large number of items to obtain the balance score and balance level, which is less efficient and redundant. In t...
Computational intelligence and neuroscience
Sep 21, 2022
Due to the development of computer vision technology and image processing technology, obstacle recognition technology has been widely used in military and scientific research fields. However, most of the existing image-based recognition technologies ...
Computational intelligence and neuroscience
Sep 21, 2022
In order to solve the problems of machine translation efficiency and translation quality, this paper proposes an English translation evaluation system based on the BP neural network algorithm. This method provides users with a more intelligent machin...
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