Empowering things with intelligence: a survey of the progress, challenges, and opportunities in artificial intelligence of things
In the Internet-of-Things (IoT) era, billions of sensors and devices collect and process data
from the environment, transmit them to cloud centers, and receive feedback via the Internet …
from the environment, transmit them to cloud centers, and receive feedback via the Internet …
A comprehensive review of object detection with deep learning
R Kaur, S Singh - Digital Signal Processing, 2023 - Elsevier
In the realm of computer vision, Deep Convolutional Neural Networks (DCNNs) have
demonstrated excellent performance. Video Processing, Object Detection, Image …
demonstrated excellent performance. Video Processing, Object Detection, Image …
Towards large-scale small object detection: Survey and benchmarks
With the rise of deep convolutional neural networks, object detection has achieved
prominent advances in past years. However, such prosperity could not camouflage the …
prominent advances in past years. However, such prosperity could not camouflage the …
Small-object detection based on YOLOv5 in autonomous driving systems
With the rapid advancements in the field of autonomous driving, the need for faster and more
accurate object detection frameworks has become a necessity. Many recent deep learning …
accurate object detection frameworks has become a necessity. Many recent deep learning …
CCTSDB 2021: a more comprehensive traffic sign detection benchmark
J Zhang, X Zou, LD Kuang, J Wang… - Human-centric …, 2022 - centaur.reading.ac.uk
Traffic signs are one of the most important information that guide cars to travel, and the
detection of traffic signs is an important component of autonomous driving and intelligent …
detection of traffic signs is an important component of autonomous driving and intelligent …
No-reference image quality assessment via transformers, relative ranking, and self-consistency
Abstract The goal of No-Reference Image Quality Assessment (NR-IQA) is to estimate the
perceptual image quality in accordance with subjective evaluations, it is a complex and …
perceptual image quality in accordance with subjective evaluations, it is a complex and …
Improved YOLOv5 network for real-time multi-scale traffic sign detection
Traffic sign detection is a challenging task for the unmanned driving system, especially for
the detection of multi-scale targets and the real-time problem of detection. In the traffic sign …
the detection of multi-scale targets and the real-time problem of detection. In the traffic sign …
Recent advances in deep learning for object detection
Object detection is a fundamental visual recognition problem in computer vision and has
been widely studied in the past decades. Visual object detection aims to find objects of …
been widely studied in the past decades. Visual object detection aims to find objects of …
Deep multi-modal object detection and semantic segmentation for autonomous driving: Datasets, methods, and challenges
Recent advancements in perception for autonomous driving are driven by deep learning. In
order to achieve robust and accurate scene understanding, autonomous vehicles are …
order to achieve robust and accurate scene understanding, autonomous vehicles are …
Recent advances in small object detection based on deep learning: A review
Small object detection is a challenging problem in computer vision. It has been widely
applied in defense military, transportation, industry, etc. To facilitate in-depth understanding …
applied in defense military, transportation, industry, etc. To facilitate in-depth understanding …