Probabilistic mass-mapping with neural score estimation

Comparison of disability score estimation in multiple sclerosis patients with artificial neural network and decision tree models

Background: Multiple Sclerosis (MS) is one of the most debilitating disease among young adults. Understanding the disability score (Expanded Disability Status Scale (EDSS)) of these patients is helpful in choosing their treatment process. Calculating EDSS takes a lot of time for Neurologists, so having a way to estimate EDSS can be helpful. This study aimed to estimate the EDSS score of MS pati...

Probabilistic Mapping of Human Visual Attention from Head Pose Estimation

Effective interaction between a human and a robot requires the bidirectional perception and interpretation of actions and behavior. While actions can be identified as a directly observable activity, this might not be sufficient to deduce actions in a scene. For example, orienting our face toward a book might suggest the action toward “reading.” For a human observer, this deduction requires the ...

Neural Mapping with Radioautography

The availability of si~nple and reliable methods for establishing the precise distribution of specific fiber pathways within the central nervous system (CNS) has been a problem of continuing interest to the neurologist. Early neuroanatomical studies almost exclusively consisted of evaluations made in normal histological material 13. Subsequently, a number of more sophisticated tracing methods h...

Semantic Mapping with a Probabilistic Description Logic

3d Robotic Mapping with Probabilistic Occupancy Grids

We propose a new approach to 3D environment mapping from a mobile robot, using visual information provided by alow-cost stereo vision system. Depth information recovered from disparity maps serves as input for our method that uses probabilistic modelling to determine if a region is occupied or freein an occupancy grid approach. There is no similar approach in the literature, based on statistica...