Computer vision for autonomous vehicles: Problems, datasets and state of the art

J Janai, F Güney, A Behl, A Geiger - Foundations and Trends® …, 2020 - nowpublishers.com
Recent years have witnessed enormous progress in AI-related fields such as computer
vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it …

A survey on intelligent Internet of Things: Applications, security, privacy, and future directions

O Aouedi, TH Vu, A Sacco, DC Nguyen… - … surveys & tutorials, 2024 - ieeexplore.ieee.org
The rapid advances in the Internet of Things (IoT) have promoted a revolution in
communication technology and offered various customer services. Artificial intelligence (AI) …

Multi-class fruit-on-plant detection for apple in SNAP system using Faster R-CNN

F Gao, L Fu, X Zhang, Y Majeed, R Li, M Karkee… - … and Electronics in …, 2020 - Elsevier
Deep learning achieved high success of fruit-on-plant detection such as on apple. Most of
studies on apple detection identified all target fruits as one class regardless of fruit condition …

A cascaded R-CNN with multiscale attention and imbalanced samples for traffic sign detection

J Zhang, Z **e, J Sun, X Zou, J Wang - IEEE access, 2020 - ieeexplore.ieee.org
In recent years, the deep learning is applied to the field of traffic sign detection methods
which achieves excellent performance. However, there are two main challenges in traffic …

Deep convolutional neural network for enhancing traffic sign recognition developed on Yolo V4

C Dewi, RC Chen, X Jiang, H Yu - Multimedia Tools and Applications, 2022 - Springer
Traffic sign detection (TSD) is a key issue for smart vehicles. Traffic sign recognition (TSR)
contributes beneficial information, including directions and alerts for advanced driver …

Visual perception enabled industry intelligence: state of the art, challenges and prospects

J Yang, C Wang, B Jiang, H Song… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Visual perception refers to the process of organizing, identifying, and interpreting visual
information in environmental awareness and understanding. With the rapid progress of …

Efficient federated learning with spike neural networks for traffic sign recognition

K **e, Z Zhang, B Li, J Kang, D Niyato… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
With the gradual popularization of self-driving, it is becoming increasingly important for
vehicles to smartly make the right driving decisions and autonomously obey traffic rules by …

Human emotion recognition using deep belief network architecture

MM Hassan, MGR Alam, MZ Uddin, S Huda… - Information …, 2019 - Elsevier
Recently, deep learning methodologies have become popular to analyse physiological
signals in multiple modalities via hierarchical architectures for human emotion recognition …

Object detection using deep learning methods in traffic scenarios

A Boukerche, Z Hou - ACM Computing Surveys (CSUR), 2021 - dl.acm.org
The recent boom of autonomous driving nowadays has made object detection in traffic
scenes a hot topic of research. Designed to classify and locate instances in the image, this is …

An improved light-weight traffic sign recognition algorithm based on YOLOv4-tiny

L Wang, K Zhou, A Chu, G Wang, L Wang - IEEE Access, 2021 - ieeexplore.ieee.org
Aiming at the problems of low detection accuracy and inaccurate positioning accuracy of
light-weight network in traffic sign recognition task, an improved light-weight traffic sign …