Computer vision for autonomous vehicles: Problems, datasets and state of the art
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 …
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
The rapid advances in the Internet of Things (IoT) have promoted a revolution in
communication technology and offered various customer services. Artificial intelligence (AI) …
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
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 …
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 …
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
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 …
contributes beneficial information, including directions and alerts for advanced driver …
Visual perception enabled industry intelligence: state of the art, challenges and prospects
Visual perception refers to the process of organizing, identifying, and interpreting visual
information in environmental awareness and understanding. With the rapid progress of …
information in environmental awareness and understanding. With the rapid progress of …
Efficient federated learning with spike neural networks for traffic sign recognition
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 …
vehicles to smartly make the right driving decisions and autonomously obey traffic rules by …
Human emotion recognition using deep belief network architecture
Recently, deep learning methodologies have become popular to analyse physiological
signals in multiple modalities via hierarchical architectures for human emotion recognition …
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 …
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 …
light-weight network in traffic sign recognition task, an improved light-weight traffic sign …