Chenlei Guo

Microsoft · Web Search and Mining Research Area (WSM)

Distributed and local processes analyze usage data and transform it into objects including timestamps and dimensions. Objects include a position vector to represent dimension analysis and additional attributes associated with measurements of different types. The objects are stored in a multidimensional database indexed on the vector and timestamp a...

In this paper, we develop a robust signal space separation (rSSS) algorithm for real-time magnetoencephalography (MEG) data processing. rSSS is based on the spatial signal space separation (SSS) method and it applies robust regression to automatically detect and remove bad MEG channels so that the results of SSS are not distorted. We extend the exi...

We present a methodology for the automatic identification and delineation of germ-layer components in H&E stained images of teratomas derived from human and nonhuman primate embryonic stem cells. A knowledge and understanding of the biology of these cells may lead to advances in tissue regeneration and repair, the treatment of genetic and developme...

We present a methodology for the automatic identification and delineation of germ-layer components in H&E stained images of teratomas derived from human and nonhuman primate embryonic stem cells. A knowledge and understanding of the biology of these cells may lead to advances in tissue regeneration and repair, the treatment of genetic and developme...

Salient areas in natural scenes are generally regarded as areas which the human eye will typically focus on, and finding these areas is the key step in object detection. In computer vision, many models have been proposed to simulate the behavior of eyes such as SaliencyToolBox (STB), Neuromorphic Vision Toolkit (NVT), and others, but they demand hi...

Salient areas in natural scenes are generally regarded as the candidates of attention focus in human eyes, which is the key stage in object detection. In computer vision, many models have been proposed to simulate the behav- ior of eyes such as SaliencyToolBox (STB), Neuromorphic Vision Toolkit (NVT) and etc., but they demand high com- putational c...

In this paper, an attention selection model with visual memory and online learning is proposed, which has three parts: Sensory Mapping (SM), Cognitive Mapping (CM) and Motor Mapping (MM). CM is the novelty of our model which incorporates visual memory and online learning. In order to mimic visual memory, we put forward an Amnesic Incremental Hierac...

This paper proposes a novel attention selection system with competition neural network supervised by visual memory. As compared with others, this system can not only attend some salient regions randomly according to sensory information but also mainly focus on some learned objects by the visual memory. So it can be applied in robot self-localizatio...

In this paper an attention selection system based on neural network is proposed, which combines supervised and unsupervised learning reasonably. A value system and memory tree with update ability are regarded as teachers to adjust the weights of neural network. Both bottom-up and top-down part are to simulate two-stage hypothesis of attention selec...