Solving the security problem of intelligent transportation system with deep learning
Z Lv, S Zhang, W Xiu - IEEE Transactions on Intelligent …, 2020 - ieeexplore.ieee.org
Objective: the objective of this study is to study deep learning to solve the safety problems of
intelligent transportation system. Method: the intelligent transportation system is improved by …
intelligent transportation system. Method: the intelligent transportation system is improved by …
Sentiment analysis of Arabic tweets in smart cities: A review of Saudi dialect
Social media including Twitter have transformed our societies and has become an important
pulse of smart societies by sensing the information about the people and their experiences …
pulse of smart societies by sensing the information about the people and their experiences …
Smarter traffic prediction using big data, in-memory computing, deep learning and GPUs
Road transportation is the backbone of modern economies, albeit it annually costs 1.25
million deaths and trillions of dollars to the global economy, and damages public health and …
million deaths and trillions of dollars to the global economy, and damages public health and …
Towards deep learning based smart farming for intelligent weeds management in crops
Introduction Deep learning (DL) is a core constituent for building an object detection system
and provides a variety of algorithms to be used in a variety of applications. In agriculture …
and provides a variety of algorithms to be used in a variety of applications. In agriculture …
Rapid transit systems: smarter urban planning using big data, in-memory computing, deep learning, and GPUs
Rapid transit systems or metros are a popular choice for high-capacity public transport in
urban areas due to several advantages including safety, dependability, speed, cost, and …
urban areas due to several advantages including safety, dependability, speed, cost, and …
Short-term traffic flow prediction based on LSTM-XGBoost combination model
X Zhang, Q Zhang - Computer Modeling in Engineering & …, 2020 - ingentaconnect.com
According to the time series characteristics of the trajectory history data, we predicted and
analyzed the traffic flow. This paper proposed a LSTM-XGBoost model based urban road …
analyzed the traffic flow. This paper proposed a LSTM-XGBoost model based urban road …
TAAWUN: A decision fusion and feature specific road detection approach for connected autonomous vehicles
Road transportation is among the global grand challenges affecting human lives, health,
society, and economy, caused due to road accidents, traffic congestion, and other …
society, and economy, caused due to road accidents, traffic congestion, and other …
[PDF][PDF] Predicting stock closing prices in emerging markets with transformer neural networks: The saudi stock exchange case
Deep learning has transformed many fields including computer vision, self-driving cars,
product recommendations, behaviour analysis, natural language processing (NLP), and …
product recommendations, behaviour analysis, natural language processing (NLP), and …
ZAKI: A smart method and tool for automatic performance optimization of parallel SpMV computations on distributed memory machines
SpMV is a vital computing operation of many scientific, engineering, economic and social
applications, increasingly being used to develop timely intelligence for the design and …
applications, increasingly being used to develop timely intelligence for the design and …
ZAKI+: A machine learning based process mapping tool for SpMV computations on distributed memory architectures
Smart cities and other cyber-physical systems (CPSs) rely on various scientific, engineering,
business, and social applications that provide timely intelligence for their design, operations …
business, and social applications that provide timely intelligence for their design, operations …