62 citations · 129 across the 18 of their papers we have counts for
5 papers · 1 filter
Multiple Instance Learning for Brain Tumor Detection from Magnetic Resonance Spectroscopy Data
Diyuan Lu, Gerhard Kurz, Nenad Polomac +3
We apply deep learning (DL) on Magnetic resonance spectroscopy (MRS) data for the task of brain tumor detection. Medical applications often suffer from data scarcity and corruption…
Recurrent Feedback Improves Recognition of Partially Occluded Objects
Markus Roland Ernst, Jochen Triesch, Thomas Burwick
Recurrent connectivity in the visual cortex is believed to aid object recognition for challenging conditions such as occlusion. Here we investigate if and how artificial neural net…
Learning Hierarchical Integration of Foveal and Peripheral Vision for Vergence Control by Active Efficient Coding
Zhetuo Zhao, Jochen Triesch, Bertram E. Shi
The active efficient coding (AEC) framework parsimoniously explains the joint development of visual processing and eye movements, e.g., the emergence of binocular disparity selecti…
Self-Calibrating Active Binocular Vision via Active Efficient Coding with Deep Autoencoders
Charles Wilmot, Bertram E. Shi, Jochen Triesch
We present a model of the self-calibration of active binocular vision comprising the simultaneous learning of visual representations, vergence, and pursuit eye movements. The model…
Learning Abstract Representations through Lossy Compression of Multi-Modal Signals
Charles Wilmot, Gianluca Baldassarre, Jochen Triesch
A key competence for open-ended learning is the formation of increasingly abstract representations useful for driving complex behavior. Abstract representations ignore specific det…