Most high-level computer vision tasks rely on low-level image operations as their initial
processes. Operations such as edge detection, image enhancement, and super-resolution …

Deep learning currently rules edge detection. However, the impressive progress heavily
relies on high-quality manually annotated labels which require a significant amount of labor …

This paper presents a Lightweight Dense Convolutional (LDC) neural network for edge
detection. The proposed model is an adaptation of two state-of-the-art approaches, but it …

Automatic and accurate pavement crack detection is essential for cost-effective road
maintenance. Deep convolutional neural networks (DCNNs) are widely used in recent …

A new fuzzy method for creating a depth map is presented in the article. It is based on a
combination of Canny detector with a three-level fuzzy system and is designed to improve …

摘要针对传统边缘检测方法受高斯噪声, 椒盐噪声污染及边缘梯度变化幅度小等因素影响而出现
的物体轮廓检测效果不理想, 误检率, 漏检率高等问题, 提出Canny-Cauchy 边缘检测算法 …

This study sought to address the problem of the insufficient extraction of shallow object
information and boundary information when using traditional FPN structures in current object …

One of the primary causes of fires at construction sites is welding sparks. Fire detection
systems utilizing computer vision technology offer a unique opportunity to monitor fires in …

Automatic skin lesion segmentation is the most critical and relevant task in computer‐aided
skin cancer diagnosis. Methods based on convolutional neural networks (CNNs) are mainly …

In this article, a hierarchical method for action recognition based on temporal and spatial
features is proposed. In current HAR methods, camera movement, sensor movement …