The evolution of mobile mapping systems (MMSs) has gained more attention in the past few
decades. MMSs have been widely used to provide valuable assets in different applications …

In the past decade, autonomous vehicle systems (AVS) have advanced at an exponential
rate, particularly due to improvements in artificial intelligence, which have had a significant …

The first edition of this textbook was published in 2021. Over the past two years, we have
invested in enhancing all aspects of deep learning methods to ensure the book is …

The goal of human action recognition is to identify and understand the actions of people in
videos and export corresponding tags. In addition to spatial correlation existing in 2D …

Traffic-sign recognition (TSR) has been an essential part of driver-assistance systems, which
is able to assist drivers in avoiding a vast number of potential hazards and improve the …

In this paper, ConvNeXt is selected as a model for waste classification from digital images.
ConvNeXt is a CNN-based backbone network that has been proposed to further improve the …

With the popularity of autonomous driving, the development of ADAS (Advanced Driver
Assistance Systems), especially collision avoidance systems, has become an important …

A fully connected layer is essential for a CNN, ie, convolutional neural network, which has
been shown to be successful in classifying images in several related applications. A CNN …

In challenging lighting conditions, such as haze, rain, and weak lighting condition, the
accuracy of traffic sign recognition is not very high due to missed detection or incorrect …

In this paper, we investigate the problem of human behavior recognition by using the state-of-
the-art deep learning methods. In order to achieve sufficient recognition accuracy, both …