PUBLICATIONS

Search Filters
 (complete or partial)
 (complete or partial)
Filter By Year (slide to select)
Start: 2008 End: 2016

Reset
Sort By:

We examine hierarchical approaches to image classification problems that include categories for which we have no training examples. Building on prior work in hierarchical classification that optimizes the trade-off between depth in a tree and accuracy of placement, we compare the performance of multiple formulations of the problem on both previous   ...more

Our objective was to compare the effectiveness of applying the historical limits method (HLM) to poison center (PC) call volumes with vs without stratifying by exposure type.   ...more

This work leverages Deep Reinforcement Learning (DRL) to make robotic control immune to changes in the robot manipulator or the environment and to perform reaching, collision avoidance and grasping without explicit, prior and fine knowledge of the human arm structure and kinematics, without careful hand-eye calibration, solely based on visual/reti   ...more

This study addresses the development of machine learning methods for reduced space ultrasound to perform automated prescreening of breast cancer. The use of ultrasound in low-resource settings is constrained by lack of trained personnel and equipment costs, and motivates the need for automated, low-cost diagnostic tools. We hypothesize a solution   ...more

The development of portable non-invasive brain computer interface technologies with higher spatio-temporal resolution has been motivated by the tremendous success seen with implanted devices. This talk will discuss efforts to overcome several major obstacles to viability including approaches that promise to improve spatial and temporal resolution.   ...more

Purpose: In minimally invasive interventions assisted by C-arm imaging, there is a demand to fuse the intra-interventional 2D C-arm image with pre-interventional 3D patient data to enable surgical guidance. The commonly used intensity-based 2D/3D registration has a limited capture range and is sensitive to initialization. We propose to utilize an   ...more

Contact Us


Chief
Ashley Llorens
Ashley.Llorens@jhuapl.edu
240-228-0312

Physical Address
7701 Montpelier Road
Laurel, MD 20723


The Intelligent Systems Center is located at the Montpelier Campus of the Johns Hopkins Applied Physics Laboratory.
Click here for a map, directions and other visitor information.