Autonomous vehicles have become a topic of interest in recent times due to the rapid
advancement of automobile and computer vision technology. The ability of autonomous …

For practitioners, it is very crucial to realize accurate and automatic vision-based quality
identification of Longjing tea. Due to the high similarity between classes, the classification …

Traffic sign recognition techniques aim to reduce the probability of traffic accidents by
increasing road and vehicle safety. These systems play an essential role in the development …

With the growing trend in autonomous vehicles, accurate recognition of traffic signs has
become crucial. This research focuses on the use of convolutional neural networks for traffic …

In digital image processing, filtering noise is an important step for reconstructing a high-
quality image for further processing such as object segmentation, object detection, and …

The increasing use of unmanned aerial vehicles (UAVs) in both military and civilian
applications, such as infrastructure inspection, package delivery, and recreational activities …

Traffic forecasting stands as a cornerstone in urban planning, yet existing methods mainly
fall short in capturing long-term spatio-temporal patterns. To be specific, various exquisite …

Glaucoma, a disease that damages the optic nerve, is the leading cause of irreversible
blindness worldwide. The early detection of glaucoma is a challenge, which in recent years …

In this paper, we propose a cross-domain few-shot in-context learning method based on the
multimodal large language model (MLLM) for enhancing traffic sign recognition (TSR). We …

Accurate traffic sign data recognition is crucial for enhancing safety in autonomous driving
system. However, recognizing traffic signs from natural scenes is challenging due to factors …