Biometric systems are used for the verification and identification of individuals using their
physiological or behavioral features. These features can be categorized into unimodal and …

Object detection is one of the most challenging tasks in computer vision. With the advances
in semiconductor devices and chip technology, hardware accelerators have been widely …

Deep convolutional neural networks (CNNs) have attracted considerable interest in low-
level computer vision. Researches are usually devoted to improving the performance via …

Facial expression recognition has become a hot issue in the field of artificial intelligence. So,
we collect literature on facial expression recognition. First, methods based on machine …

Conventional graph based clustering methods treat all features equally even if they are
redundant features or noise in the stage of graph learning, which is obviously unreasonable …

Abstract Recently, Multi-view Discriminant Analysis (MVDA) has been proposed and
achieves good performance in multi-view recognition tasks. However, as an extension of …

Ridge regression is widely used in multiple variable data analysis. However, in very high-
dimensional cases such as image feature extraction and recognition, conventional ridge …

摘要能否及时诊断出微小故障是保障系统安全运行并抑制故障恶化的关键,
本文针对微小故障幅值低, 易被系统扰动和噪声掩盖等特点, 从数据驱动的角度对现有研究进行 …

For sparse representation or sparse coding based image classification, the dictionary, which
is required to faithfully and robustly represent query images, plays an important role on its …

In this study, classification performance of histopathological images which are processed by
pre-processing algorithms using convolutional neural network structure is examined. The …