Abstract Anomalies (or outliers) indicate a minority of data items that are quite different from the majority (inliers) dataset in certain aspect. Unsupervised anomaly detection (UAD) is an important but not yet extensively studied research topic. Recent deep learning based methods exploit reconstruction gap between inliers and outliers to discriminate them. However, it observed often decreases...

Pedestrian detection in the wild remains a challenging problem especially for scenes containing serious occlusion. In this paper, we propose novel feature learning method deep framework, referred to as Feature Calibration Network (FC-Net), adaptively detect pedestrians under various occlusions. FC-Net is based on observation that visible parts of are selective and decisive detection, implemente...

In general object detection, scale variation is always a big challenge. At present, feature pyramid networks are employed in numerous methods to alleviate the problems caused by large range of objects which makes use multi-level features extracted from backbone for top-down upsampling and fusion acquire set multi-scale depth image features. However, network proposed Ghiasi et al. adopts simple ...

Abstract Sequential X-ray photon correlation spectroscopy (XPCS) reveals sample dynamics by analyzing a series of coherent scattering images, which is often time-consuming. For applications like real-time XPCS analysis, high efficiency desired. Pixel binning straightforward strategy to reduce the processing time, but over-binning may result in an insufficient signal-to-noise ratio. In this work...

The problem of logo recognition is of great interest in the document domain, especially for databases, because of its potential for identifying the source of the document and its generality as a recognition problem. By recognizing the logo we obtain semantic information about the document, which may be useful in deciding whether or not to analyze the textual components. In this paper, we presen...

In this paper, we discuss an image modelling method that can capture and represent a number of commonly used image characteristics such as lines, blobs, statistical and structural textures. We develop the concepts underlying the Kadir and Brady feature detection algorithm [2], namely feature space unpredictability and spatial localisation, to characterise, what is termed, the semilocal predicta...

This paper presents a robust and adaptable facial feature extraction system used for facial expression recognition in humancomputer interaction (HCI) environments. Such environments are usually uncontrolled in terms of lighting and color quality, as well as human expressivity and movement; as a result, using a single feature extraction technique may fail in some parts of a video sequence, while...