[HTML][HTML] Unsupervised machine learning in urban studies: A systematic review of applications

J Wang, F Biljecki - Cities, 2022 - Elsevier
Unsupervised learning (UL) has a long and successful history in untangling the complexity
of cities. As the counterpart of supervised learning, it discovers patterns from intrinsic data …

Leveraging Deep Learning and IoT big data analytics to support the smart cities development: Review and future directions

SB Atitallah, M Driss, W Boulila, HB Ghézala - Computer Science Review, 2020 - Elsevier
The rapid growth of urban populations worldwide imposes new challenges on citizens' daily
lives, including environmental pollution, public security, road congestion, etc. New …

A review of vision-based traffic semantic understanding in ITSs

J Chen, Q Wang, HH Cheng, W Peng… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
A semantic understanding of road traffic can help people understand road traffic flow
situations and emergencies more accurately and provide a more accurate basis for anomaly …

Greedy hierarchical variational autoencoders for large-scale video prediction

B Wu, S Nair, R Martin-Martin… - Proceedings of the …, 2021 - openaccess.thecvf.com
A video prediction model that generalizes to diverse scenes would enable intelligent agents
such as robots to perform a variety of tasks via planning with the model. However, while …

Deep learning for the industrial internet of things (iiot): A comprehensive survey of techniques, implementation frameworks, potential applications, and future directions

S Latif, M Driss, W Boulila, ZE Huma, SS Jamal… - Sensors, 2021 - mdpi.com
The Industrial Internet of Things (IIoT) refers to the use of smart sensors, actuators, fast
communication protocols, and efficient cybersecurity mechanisms to improve industrial …

Anomaly detection using edge computing in video surveillance system

DR Patrikar, MR Parate - International Journal of Multimedia Information …, 2022 - Springer
The current concept of smart cities influences urban planners and researchers to provide
modern, secured and sustainable infrastructure and gives a decent quality of life to its …

A review of artificial intelligence and machine learning for incident detectors in road transport systems

S Olugbade, S Ojo, AL Imoize, J Isabona… - Mathematical and …, 2022 - mdpi.com
Road transport is the most prone to accidents, resulting in significant fatalities and injuries. It
also faces a plethora of never-ending problems, such as the frequent loss of lives and …

Anomaly detection in road traffic using visual surveillance: A survey

KK Santhosh, DP Dogra, PP Roy - ACM Computing Surveys (CSUR), 2020 - dl.acm.org
Computer vision has evolved in the last decade as a key technology for numerous
applications replacing human supervision. Timely detection of traffic violations and …

Applications of deep learning in intelligent transportation systems

AK Haghighat, V Ravichandra-Mouli… - Journal of Big Data …, 2020 - Springer
Abstract In recent years, Intelligent Transportation Systems (ITS) have seen efficient and
faster development by implementing deep learning techniques in problem domains which …

RCNet: road classification convolutional neural networks for intelligent vehicle system

DK Dewangan, SP Sahu - Intelligent Service Robotics, 2021 - Springer
Vision-based techniques for intelligent vehicles in heterogeneous road environments are
gaining significant attention from researchers and industrialists. Unfortunately, the …