|
|
|
|
|
Hellena Hempe, Alexander Bigalke and Mattias Paul Heinrich
Background: Degenerative spinal pathologies are highly prevalent among the elderly population. Timely diagnosis of osteoporotic fractures and other degenerative deformities enables proactive measures to mitigate the risk of severe back pain and disabilit...
ver más
|
|
|
|
|
|
|
|
|
|
|
Chinyang Henry Tseng, Woei-Jiunn Tsaur and Yueh-Mao Shen
In detecting large-scale attacks, deep neural networks (DNNs) are an effective approach based on high-quality training data samples. Feature selection and feature extraction are the primary approaches for data quality enhancement for high-accuracy intrus...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yingying Liang, Peng Zhao and Yimeng Wang
Deep learning has undergone significant progress for machinery fault diagnosis in the Industrial Internet of Things; however, it requires a substantial amount of labeled data. The lack of sufficient fault samples in practical applications remains a chall...
ver más
|
|
|
|
|
|
|
|
|
|
|
Zhuo Wang, Haojie Chen, Hongde Qin and Qin Chen
In the computer vision field, underwater object detection has been a challenging task. Due to the attenuation of light in a medium and the scattering of light by suspended particles in water, underwater optical images often face the problems of color dis...
ver más
|
|
|
|
|
|
|
|
|
|
|
Dawei Luo, Heng Zhou, Joonsoo Bae and Bom Yun
Reliability and robustness are fundamental requisites for the successful integration of deep-learning models into real-world applications. Deployed models must exhibit an awareness of their limitations, necessitating the ability to discern out-of-distrib...
ver más
|
|
|
|
|
|
|
|
|
|
|
Junwen Lu, Jinhui Wang, Xiaojun Wei, Keshou Wu and Guanfeng Liu
There is relatively little research on deep learning for anomaly detection within the field of deep learning. Existing deep anomaly detection methods focus on the learning of feature reconstruction, but such methods mainly learn new feature representatio...
ver más
|
|
|
|
|
|
|
|
|
|
|
Ashish Bagwari, Anurag Sinha, N. K. Singh, Namit Garg and Jyotshana Kanti
Business-based decision support systems have been proposed for a few decades in the e-commerce and textile industries. However, these Decision Support Systems (DSS) have not been so productive in terms of business decision delivery. In our proposed model...
ver más
|
|
|
|
|
|
|
|
|
|
|
Theiab Alzahrani, Baidaa Al-Bander and Waleed Al-Nuaimy
Makeup can disguise facial features, which results in degradation in the performance of many facial-related analysis systems, including face recognition, facial landmark characterisation, aesthetic quantification and automated age estimation methods. Thu...
ver más
|
|
|
|
|
|
|
|
|
|
|
Lin-Huang Chang, Tsung-Han Lee, Hung-Chi Chu, Cheng-Wei Su
Pág. 216 - 229
The traffic classification based on the network applications is one important issue for network management. In this paper, we propose an application-based online and offline traffic classification, based on deep learning mechanisms, over software-defined...
ver más
|
|
|
|
|
|
|
|
|
|
|
Mou Wang, Xiao-Lei Zhang and Susanto Rahardja
Acoustic scene analysis has attracted a lot of attention recently. Existing methods are mostly supervised, which requires well-predefined acoustic scene categories and accurate labels. In practice, there exists a large amount of unlabeled audio data, but...
ver más
|
|
|
|
|
|