Semantic segmentation network-based methods can detect concrete damage at the pixel level. However, the performance of a single semantic segmentation network is often limited. To improve the concrete damage detection performance of a semantic segment...
With humanity entering the age of intelligence, text detection technology has been gradually applied in the industry. However, text detection in a complex background is still a challenging problem for researchers to overcome. Most of the current algo...
Multitask learning (MTL) is an open and challenging problem in various real-world applications, such as recommendation systems, natural language processing, and computer vision. The typical way of conducting multitask learning is establishing some gl...
How is knowledge about word meaning represented in the mental lexicon? Current computational models infer word meanings from lexical co-occurrence patterns. They learn to represent words as vectors in a multidimensional space, wherein words that are ...
Computational intelligence and neuroscience
Apr 13, 2022
Obscuring or otherwise minimizing the release of personality information from potential victims of social engineering attacks effectively interferes with an attacker's personality analysis and reduces the success rate of social engineering attacks. W...
Annali di igiene : medicina preventiva e di comunita
Apr 12, 2022
BACKGROUND: Nurses record data in electronic health records (EHRs) using different terminologies and coding systems. The purpose of this study was to identify unstructured free-text nursing activities recorded by nurses in EHRs with natural language ...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Apr 11, 2022
Deep feature embedding aims to learn discriminative features or feature embeddings for image samples which can minimize their intra-class distance while maximizing their inter-class distance. Recent state-of-the-art methods have been focusing on lear...
In the paper, we proposed a deep learning-based industrial equipment detection algorithm ROMS R-CNN (Rotation Occlusion Multi-Scale Region-CNN). It can solve the problem of inaccurate detection of industrial equipment under complex working conditions...
IEEE transactions on neural networks and learning systems
Apr 4, 2022
Recently, there has been a surge of interest in applying memristors to hardware implementations of deep neural networks due to various desirable properties of the memristor, such as nonvolativity, multivalue, and nanosize. Most existing neural networ...
Few-shot learning (FSL) is of great significance to the field of machine learning. The ability to learn and generalize using a small number of samples is an obvious distinction between artificial intelligence and humans. In the FSL domain, most graph...