Computational intelligence and neuroscience
Jun 25, 2022
People are actively expressing their views and opinions via the use of visual pictures and text captions on social media platforms, rather than just publishing them in plain text as a consequence of technical improvements in this field. With the adve...
This study proposes a simple convolutional neural network (CNN)-based model for vehicle classification in low resolution surveillance images collected by a standard security camera installed distant from a traffic scene. In order to evaluate its effe...
Computational intelligence and neuroscience
Jun 20, 2022
In this paper, a multimodal knowledge mapping approach is used to digitize enterprise carbon assets, and a corresponding neural network model is designed for use in the practical process. Rich textual entity labels associated with images are obtained...
It is a well-established practice to build a robust system for sound event detection by training supervised deep learning models on large datasets, but audio data collection and labeling are often challenging and require large amounts of effort. This...
BACKGROUND: Real-world data (RWD) is increasingly being embraced as an invaluable source of information to address clinical and policy-relevant questions that are unlikely to ever be answered by clinical trials. However, the largely unrealised potent...
The fundamental goal of artificial intelligence (AI) is to mimic the core cognitive activities of human. Despite tremendous success in the AI research, most of existing methods have only single-cognitive ability. To overcome this limitation and take ...
Computational intelligence and neuroscience
May 26, 2022
Diseases and pests are essential threat factors that affect agricultural production, food security supply, and ecological plant diversity. However, the accurate recognition of various diseases and pests is still challenging for existing advanced info...
Training on multiple diverse data sources is critical to ensure unbiased and generalizable AI. In healthcare, data privacy laws prohibit data from being moved outside the country of origin, preventing global medical datasets being centralized for AI ...
Data-driven rolling-bearing fault diagnosis methods are mostly based on deep-learning models, and their multilayer nonlinear mapping capability can improve the accuracy of intelligent fault diagnosis. However, problems such as gradient disappearance ...
International journal of environmental research and public health
May 23, 2022
Recognizing why an infant cries is challenging as babies cannot communicate verbally with others to express their wishes or needs. This leads to difficulties for parents in identifying the needs and the health of their infants. This study used deep l...