An enhanced extreme learning machine model for river flow forecasting: State-of-the-art, practical applications in water resource engineering area and future research …
Despite the massive diversity in the modeling requirements for practical hydrological
applications, there remains a need to develop more reliable and intelligent expert systems …
applications, there remains a need to develop more reliable and intelligent expert systems …
A review on neural networks with random weights
In big data fields, with increasing computing capability, artificial neural networks have shown
great strength in solving data classification and regression problems. The traditional training …
great strength in solving data classification and regression problems. The traditional training …
Robust lane detection from continuous driving scenes using deep neural networks
Lane detection in driving scenes is an important module for autonomous vehicles and
advanced driver assistance systems. In recent years, many sophisticated lane detection …
advanced driver assistance systems. In recent years, many sophisticated lane detection …
Digital twin integrated reinforced learning in supply chain and logistics
Background: As the Internet of Things (IoT) has become more prevalent in recent years,
digital twins have attracted a lot of attention. A digital twin is a virtual representation that …
digital twins have attracted a lot of attention. A digital twin is a virtual representation that …
Machine learning models and techniques for VANET based traffic management: Implementation issues and challenges
Low latency in communication among the vehicles and RSUs, smooth traffic flow, and road
safety are the major concerns of the Intelligent Transportation Systems. Vehicular Ad hoc …
safety are the major concerns of the Intelligent Transportation Systems. Vehicular Ad hoc …
A survey on theories and applications for self-driving cars based on deep learning methods
J Ni, Y Chen, Y Chen, J Zhu, D Ali, W Cao - Applied Sciences, 2020 - mdpi.com
Self-driving cars are a hot research topic in science and technology, which has a great
influence on social and economic development. Deep learning is one of the current key …
influence on social and economic development. Deep learning is one of the current key …
Attentional feature pyramid network for small object detection
K Min, GH Lee, SW Lee - Neural Networks, 2022 - Elsevier
Recent state-of-the-art detectors generally exploit the Feature Pyramid Networks (FPN) due
to its advantage of detecting objects at different scales. Despite significant advances in …
to its advantage of detecting objects at different scales. Despite significant advances in …
Software defect prediction based on enhanced metaheuristic feature selection optimization and a hybrid deep neural network
K Zhu, S Ying, N Zhang, D Zhu - Journal of Systems and Software, 2021 - Elsevier
Software defect prediction aims to identify the potential defects of new software modules in
advance by constructing an effective prediction model. However, the model performance is …
advance by constructing an effective prediction model. However, the model performance is …
Advances in vision-based lane detection: Algorithms, integration, assessment, and perspectives on ACP-based parallel vision
Lane detection is a fundamental aspect of most current advanced driver assistance systems
(ADASs). A large number of existing results focus on the study of vision-based lane …
(ADASs). A large number of existing results focus on the study of vision-based lane …
Computational models for clinical applications in personalized medicine—guidelines and recommendations for data integration and model validation
The future development of personalized medicine depends on a vast exchange of data from
different sources, as well as harmonized integrative analysis of large-scale clinical health …
different sources, as well as harmonized integrative analysis of large-scale clinical health …