UAV sensor data applications with deep neural networks: a comprehensive survey
Abstract The use of Unmanned Aerial Vehicles (UAVs) has become increasingly popular in
recent years, leading to a surge in research on this topic that is widely represented in the …
recent years, leading to a surge in research on this topic that is widely represented in the …
Real-time vehicle detection algorithm based on a lightweight You-Only-Look-Once (YOLOv5n-L) approach
M Bie, Y Liu, G Li, J Hong, J Li - Expert Systems with Applications, 2023 - Elsevier
A vehicle detection algorithm is of great significance for automatic driving technology.
Current vehicle detection algorithms suffer from the complex structure, high configuration of …
Current vehicle detection algorithms suffer from the complex structure, high configuration of …
Subspace-based minority oversampling for imbalance classification
In pattern classification, the class imbalance problem always occurs when the number of
observations in some classes is significantly different from that of other categories, which …
observations in some classes is significantly different from that of other categories, which …
Zero-carbon measure prioritization for sustainable freight transport using interval 2 tuple linguistic decision approaches
Freight transport is the main source of carbon emissions. Implementing freight transport zero-
carbon measures in an orderly manner has a very important practical value for sustainable …
carbon measures in an orderly manner has a very important practical value for sustainable …
Mul-DesLSTM: An integrative multi-time granularity deep learning prediction method for urban rail transit short-term passenger flow
W Lu, Y Zhang, P Li, T Wang - Engineering Applications of Artificial …, 2023 - Elsevier
It is critical for the management and control of urban rail transit (URT) to be able to predict
passenger flow accurately and in real time. Considering that the high-resolution data …
passenger flow accurately and in real time. Considering that the high-resolution data …
Computer vision for hunting stability inspection of high-speed trains
The existing online inspection methods for hunting motion of high-speed trains are mainly
based on processing the acceleration of bogie frames, which cannot directly and reliably …
based on processing the acceleration of bogie frames, which cannot directly and reliably …
Deep spatial-temporal travel time prediction model based on trajectory feature
Research on travel time prediction shows its importance in the rational planning of travel
arrangements and traffic congestion mitigation. The scale of taxi and online ride-hailing …
arrangements and traffic congestion mitigation. The scale of taxi and online ride-hailing …
Domain adaptation via Transferable Swin Transformer for tire defect detection
Y Zhang, Y Wang, Z Jiang, L Zheng, J Chen… - … Applications of Artificial …, 2023 - Elsevier
In data-driven tire defect detection, scarce defect samples and the poor transferability of
models make the defect detection a time-consuming and expensive process. In recent years …
models make the defect detection a time-consuming and expensive process. In recent years …
Rail surface defect detection using a transformer-based network
Abstract The detection of Rail Surface Defects (RSDs) plays a critical role in railway track
maintenance. Traditional image processing methods exhibit limitations due to their intricate …
maintenance. Traditional image processing methods exhibit limitations due to their intricate …
Optimal control of non-holonomic robotic systems based on type-3 fuzzy model
L Wu, H Huang, M Wang, KA Alattas… - IEEE …, 2023 - ieeexplore.ieee.org
The paper studies the control of wheeled land mobile robots (MRs) using nonlinear
equations and non-holonomic dynamic constraints. Due to the complex and unpredictable …
equations and non-holonomic dynamic constraints. Due to the complex and unpredictable …