With the advances in scientific foundations and technological implementations, optical
metrology has become versatile problem-solving backbones in manufacturing, fundamental …

Object detection or localization is an incremental step in progression from coarse to fine
digital image inference. It not only provides the classes of the image objects, but also …

Hodykin-Huxley 方程, 感知器模型与自适应滤波器, 再到六十年代的自组织映射网络,
神经认知机, 自适应共振网络, 许多神经计算模型都发展成为信号处理, 计算机视觉 …

Deep learning is currently widely used in a variety of applications, including computer vision
and natural language processing. End devices, such as smartphones and Internet-of-Things …

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 …

With the rapid development of deep learning techniques, deep convolutional neural
networks (DCNNs) have become more important for object detection. Compared with …

In recent years, object detection has experienced impressive progress. Despite these
improvements, there is still a significant gap in the performance between the detection of …

We present a deformable prototypical part network (Deformable ProtoPNet), an interpretable
image classifier that integrates the power of deep learning and the interpretability of case …

Object detection, one of the most fundamental and challenging problems in computer vision,
seeks to locate object instances from a large number of predefined categories in natural …

Objectives Deep convolutional neural networks (CNNs) are a rapidly emerging new area of
medical research, and have yielded impressive results in diagnosis and prediction in the …