In this paper, we propose a novel text-based traffic sign detection framework with two deep
learning components. More precisely, we apply a fully convolutional network to segment …

In this paper, we introduce a new top-down framework for automatic localization and
recognition of text-based traffic guide panels (http://tinyurl. com/wiki-guide-signs) captured …

Much effort has been dedicated to text-based traffic sign detection and recognition.
However, there are still two problems. First, unlike English traffic signs with only horizontal …

Traffic sign detection plays an important role in intelligent transportation systems. But traffic
signs are still not well-detected by deep convolution neural network-based methods …

Traffic sign detection has made great progress with the rise of deep learning in recent years.
As a result of the complex and changeable traffic environment, detecting small traffic signs in …

Urban scenes are full of street entities with sign boards. Therefore, in autonomous driving,
street view text spotting techniques will play a significant role in the precise understanding of …

Although traffic sign detection has been studied for years and great progress has been
made with the rise of deep learning technique, there are still many problems remaining to be …

Traffic sign detection is an important part of environment-aware technology and has great
potential in the field of intelligent transportation. In recent years, deep learning has been …

The challenge for real-life traffic sign detection lies in recognizing small targets in a large
and complex background, making state-of-the-art general object detection methods not work …

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 …