The final loss function in the deep learning neural network is composed of other functions in the network. Due to the existence of a large number of non-linear functions such as activation functions in the network, the entire deep learning model pres...
Computational and mathematical methods in medicine
Feb 18, 2022
Event-related potentials (ERPs) can reflect the high-level thinking activities of the brain. In ERP analysis, the superposition and averaging method is often used to estimate ERPs. However, the single-trial ERP estimation can provide researchers with...
Computational intelligence and neuroscience
Feb 18, 2022
With the increased development of information technology, almost all the sectors have been developed. Age, educational qualifications, gender, and other factors have no bearing on acquiring knowledge in information technology.Most humans use mobile p...
Computational intelligence and neuroscience
Feb 18, 2022
This study aims to arouse students' interest in physical education (PE) in response to President Xi Jinping's call to strengthen students' physical quality because cultural courses occupy PE classes. Problem-based learning (PBL) is introduced, and a ...
Keratoconus is the corneal disease with the highest reported incidence of 1:2000. The treatment's level of success highly depends on how early it was started. Subsequently, a fast and highly capable diagnostic tool is crucial. While there are many co...
Knowledge Distillation (KD) is one of the widely known methods for model compression. In essence, KD trains a smaller student model based on a larger teacher model and tries to retain the teacher model's level of performance as much as possible. Howe...
Human identification of unknown samples following disaster and mass casualty events is essential, especially to bring closure to family and friends of the deceased. Unfortunately, victim identification is often challenging for forensic investigators ...
Financial portfolio management (PM) is one of the most applicable problems in reinforcement learning (RL) owing to its sequential decision-making nature. However, existing RL-based approaches rarely focus on scalability or reusability to adapt to the...
BACKGROUND: Translating research outputs into practical tools for medical practitioners is a neglected area and could have a substantial impact. One of the barriers to implementing artificial intelligence (AI) and machine learning (ML) applications i...
A crucial step in analysing text data is the detection and removal of invalid texts (e.g., texts with meaningless or irrelevant content). To date, research topics that rely heavily on analysis of text data, such as autobiographical memory, have lacke...
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