[HTML][HTML] Urban traffic flow prediction techniques: A review

B Medina-Salgado, E Sánchez-DelaCruz… - … Informatics and Systems, 2022 - Elsevier
In recent decades, the development of transport infrastructure has had a great development,
although traffic problems continue to spread due to increase due to the increase in the …

[HTML][HTML] Applications of deep learning in congestion detection, prediction and alleviation: A survey

N Kumar, M Raubal - Transportation Research Part C: Emerging …, 2021 - Elsevier
Detecting, predicting, and alleviating traffic congestion are targeted at improving the level of
service of the transportation network. With increasing access to larger datasets of higher …

Object detection recognition and robot grasping based on machine learning: A survey

Q Bai, S Li, J Yang, Q Song, Z Li, X Zhang - IEEE access, 2020 - ieeexplore.ieee.org
With the rapid development of machine learning, its powerful function in the machine vision
field is increasingly reflected. The combination of machine vision and robotics to achieve the …

Vehicular traffic congestion classification by visual features and deep learning approaches: a comparison

D Impedovo, F Balducci, V Dentamaro, G Pirlo - Sensors, 2019 - mdpi.com
Automatic traffic flow classification is useful to reveal road congestions and accidents.
Nowadays, roads and highways are equipped with a huge amount of surveillance cameras …

A review of AI for urban planning: Towards building sustainable smart cities

AK Jha, A Ghimire, S Thapa, AM Jha… - 2021 6th International …, 2021 - ieeexplore.ieee.org
Urban planning, in short, deals with solving the problems of the modern society. The
problems are complementary to the growing population in today's society. The problems in …

Vibration analysis in bearings for failure prevention using CNN

LA Pinedo-Sanchez, DA Mercado-Ravell… - Journal of the Brazilian …, 2020 - Springer
Timely failure detection for bearings is of great importance to prevent economic losses in the
industry. In this article we propose a method based on Convolutional Neural Networks …

Regional detection of traffic congestion using in a large-scale surveillance system via deep residual TrafficNet

P Wang, W Hao, Z Sun, S Wang, E Tan, L Li… - IEEE Access, 2018 - ieeexplore.ieee.org
Despite the huge amount of traffic surveillance videos and images have been accumulated
in the daily monitoring, deep learning approaches have been underutilized in the …

[HTML][HTML] From time series to image analysis: A transfer learning approach for night setback identification of district heating substations

F Zhang, C Bales, H Fleyeh - Journal of Building Engineering, 2021 - Elsevier
District heating plays a dominant role in the heating markets of Nordic countries. Therefore,
energy efficiency of district heating systems is of great interest to energy stakeholders …

Traffic density investigation & road accident analysis in India using deep learning

C Manchanda, R Rathi… - … international conference on …, 2019 - ieeexplore.ieee.org
Traffic congestion is a common affair in the big cities and towns. This issue is the outcome of
the rapid increase in the population and increasing number of vehicles, so predicting the …

Object detection and tracking using deep learning and artificial intelligence for video surveillance applications

HVR Aradhya - … journal of advanced computer science and …, 2019 - search.proquest.com
Data is the new oil in current technological society. The impact of efficient data has changed
benchmarks of performance in terms of speed and accuracy. The enhancement is …