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 …
An overview of traffic sign detection and classification methods
Y Saadna, A Behloul - International journal of multimedia information …, 2017 - Springer
Over the last few years, different traffic sign recognition systems were proposed. The present
paper introduces an overview of some recent and efficient methods in the traffic sign …
paper introduces an overview of some recent and efficient methods in the traffic sign …
Milestones in autonomous driving and intelligent vehicles—part ii: Perception and planning
A growing interest in autonomous driving (AD) and intelligent vehicles (IVs) is fueled by their
promise for enhanced safety, efficiency, and economic benefits. While previous surveys …
promise for enhanced safety, efficiency, and economic benefits. While previous surveys …
Deep learning for large-scale traffic-sign detection and recognition
D Tabernik, D Skočaj - IEEE transactions on intelligent …, 2019 - ieeexplore.ieee.org
Automatic detection and recognition of traffic signs plays a crucial role in management of the
traffic-sign inventory. It provides an accurate and timely way to manage traffic-sign inventory …
traffic-sign inventory. It provides an accurate and timely way to manage traffic-sign inventory …
DeepThin: A novel lightweight CNN architecture for traffic sign recognition without GPU requirements
For a safe and automated vehicle driving application, it is a prerequisite to have a robust and
highly accurate traffic sign detection system. In this paper, we proposed a novel energy …
highly accurate traffic sign detection system. In this paper, we proposed a novel energy …
Improved traffic sign detection and recognition algorithm for intelligent vehicles
J Cao, C Song, S Peng, F Xiao, S Song - Sensors, 2019 - mdpi.com
Traffic sign detection and recognition are crucial in the development of intelligent vehicles.
An improved traffic sign detection and recognition algorithm for intelligent vehicles is …
An improved traffic sign detection and recognition algorithm for intelligent vehicles is …
Traffic sign recognition based on semantic scene understanding and structural traffic sign location
Traffic sign recognition (TSR) plays an important role in driving assistance system and traffic
safety insurance. However, existing methods focus on extracting features of traffic signs and …
safety insurance. However, existing methods focus on extracting features of traffic signs and …
[PDF][PDF] 极限学习机前沿进展与趋势
徐睿， 梁循， 齐金山， 李志宇， 张树森 - 计算机学报, 2019 - cjc.ict.ac.cn
摘要极限学习机(ExtremeLearningMachine, ELM) 作为前馈神经网络学习中一种全新的训练
框架, 在行为识别, 情感识别和故障诊断等方面被广泛应用, 引起了各个领域的高度关注和深入 …
框架, 在行为识别, 情感识别和故障诊断等方面被广泛应用, 引起了各个领域的高度关注和深入 …
Mixture correntropy for robust learning
Correntropy is a local similarity measure defined in kernel space, hence can combat large
outliers in robust signal processing and machine learning. So far, many robust learning …
outliers in robust signal processing and machine learning. So far, many robust learning …
Application of EOS-ELM with binary Jaya-based feature selection to real-time transient stability assessment using PMU data
Y Li, Z Yang - IEEE Access, 2017 - ieeexplore.ieee.org
Recent studies show that pattern-recognition-based transient stability assessment (PRTSA)
is a promising approach for predicting the transient stability status of power systems …
is a promising approach for predicting the transient stability status of power systems …