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Chapter and Conference Paper
FDR-HS: An Empirical Bayesian Identification of Heterogenous Features in Neuroimage Analysis
Recent studies found that in voxel-based neuroimage analysis, detecting and differentiating “procedural bias” that are introduced during the preprocessing steps from lesion features, not only can help boost ac...
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Chapter and Conference Paper
Video Object Segmentation by Learning Location-Sensitive Embeddings
We address the problem of video object segmentation which outputs the masks of a target object throughout a video given only a bounding box in the first frame. There are two main challenges to this task. First...
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Chapter and Conference Paper
GSplit LBI: Taming the Procedural Bias in Neuroimaging for Disease Prediction
In voxel-based neuroimage analysis, lesion features have been the main focus in disease prediction due to their interpretability with respect to the related diseases. However, we observe that there exist anoth...
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Chapter and Conference Paper
Face Detection with End-to-End Integration of a ConvNet and a 3D Model
This paper presents a method for face detection in the wild, which integrates a ConvNet and a 3D mean face model in an end-to-end multi-task discriminative learning framework. The 3D mean face model is predefi...
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Chapter and Conference Paper
A Generative Method for Textured Motion: Analysis and Synthesis
Natural scenes contain rich stochastic motion patterns which are characterized by the movement of a large number of small elements, such as falling snow, raining, flying birds, firework and waterfall. In this ...
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Chapter and Conference Paper
What Are Textons?
Textons refer to fundamental micro-structures in generic natural images and thus constitute the basic elements in early (pre-attentive) visual perception. However, the word “texton” remains a vague concept in ...