Most clustering algorithms in fMRI analysis implicitly require some nontrivial assumption on data structure. Due to arbitrary distribution of fMRI time series in the temporal doma...
Models of spatial variation in images are central to a large number of low-level computer vision problems including segmentation, registration, and 3D structure detection. Often, i...
In this paper, we introduce the use of nonlinear dimension reduction for the analysis of functional neuroimaging datasets. Using a Laplacian Embedding approach, we show the power ...
This paper proposes a novel descriptor, granularitytunable
gradients partition (GGP), for human detection.
The concept granularity is used to define the spatial and angular
unce...
Yazhou Liu (Harbin Institute of Technology), Shigu...
Optical imaging is a powerful technique to map brain function in animals. In this study, we consider in vivo optical imaging of the murine olfactory bulb, using an intrinsic signa...
Dimitri Van De Ville, Brice Bathellier, Alan Carle...