Automated and autonomous vehicles are in an intensive development phase. It is a phase
that requires a lot of modelling and experimental research. Experimental research into these …

To forecast the future trend of financial activities through its rules, a convolutional neural
network (CNN) is used to forecast stock index. Firstly, a CNN stock index prediction model is …

Object detection methods aim to identify all target objects in the target image and determine
the categories and position information in order to achieve machine vision understanding …

Traditional iterative denoising methods can achieve good results, but are time consuming.
To address this problem, a non-iterative dual threshold denoising method is proposed …

Abstract Analysis of time series data has been a challenging research subject for decades.
Email traffic has recently been modelled as a time series function using a Recurrent Neural …

Given the importance of identifying key performance points in organizations, this research
intends to determine the most critical intra-and extra-organizational elements in assessing …

Autonomous driving systems have emerged with the promise of preventing accidents. The
first critical aspect of these systems is perception, where the regular practice is the use of top …

Light detection and ranging (LiDAR) sensor is attracting significant attention in the field of
smart transportation because of its ability to give depth information. It is already extensively …

Nowadays, deep learning methods based on a virtual environment are widely applied to
research and technology development for autonomous vehicle's smart sensors and devices …

To make full use of the effective discriminative information of the non-rigid 3D model, we
propose a novel multi-feature fusion method to fuse the multi-view feature and the 3D shape …