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Computational role of eccentricity dependent cortical magnification
(Center for Brains, Minds and Machines (CBMM), arXiv, 2014-06-06)
We develop a sampling extension of M-theory focused on invariance to scale and translation. Quite surprisingly, the theory predicts an architecture of early vision with increasing receptive field sizes and a high resolution ...
Representation Learning in Sensory Cortex: a theory
(Center for Brains, Minds and Machines (CBMM), 2014-11-14)
We review and apply a computational theory of the feedforward path of the ventral stream in visual cortex based on the hypothesis that its main function is the encoding of invariant representations of images. A key ...
The Compositional Nature of Event Representations in the Human Brain
(Center for Brains, Minds and Machines (CBMM), arXiv, 2014-07-14)
How does the human brain represent simple compositions of constituents: actors, verbs, objects, directions, and locations? Subjects viewed videos during neuroimaging (fMRI) sessions from which sentential descriptions of ...
Seeing What You’re Told: Sentence-Guided Activity Recognition In Video
(Center for Brains, Minds and Machines (CBMM), arXiv, 2014-05-29)
We present a system that demonstrates how the compositional structure of events, in concert with the compositional structure of language, can interplay with the underlying focusing mechanisms in video action recognition, ...
Simultaneous whole‐animal 3D imaging of neuronal activity using light‐field microscopy
(Center for Brains, Minds and Machines (CBMM), 2014-05-18)
High-speed, large-scale three-dimensional (3D) imaging of neuronal activity poses a major challenge in neuroscience. Here we demonstrate simultaneous functional imaging of neuronal activity at single-neuron resolution in ...
A normalization model of visual search predicts single trial human fixations in an object search task.
(Center for Brains, Minds and Machines (CBMM), arXiv, 2014-04-25)
When searching for an object in a scene, how does the brain decide where to look next? Theories of visual search suggest the existence of a global attentional map, computed by integrating bottom-up visual information with ...
Detect What You Can: Detecting and Representing Objects using Holistic Models and Body Parts
(Center for Brains, Minds and Machines (CBMM), arXiv, 2014-06-10)
Detecting objects becomes difficult when we need to deal with large shape deformation, occlusion and low resolution. We propose a novel approach to i) handle large deformations and partial occlusions in animals (as examples ...
Abstracts of the 2014 Brains, Minds, and Machines Summer School
(Center for Brains, Minds and Machines (CBMM), 2014-09-26)
A compilation of abstracts from the student projects of the 2014 Brains, Minds, and Machines Summer School, held at Woods Hole Marine Biological Lab, May 29 - June 12, 2014.
Human-Machine CRFs for Identifying Bottlenecks in Holistic Scene Understanding
(Center for Brains, Minds and Machines (CBMM), arXiv, 2014-06-15)
Recent trends in image understanding have pushed for holistic scene understanding models that jointly reason about various tasks such as object detection, scene recognition, shape analysis, contextual reasoning, and local ...
Parsing Semantic Parts of Cars Using Graphical Models and Segment Appearance Consistency
(Center for Brains, Minds and Machines (CBMM), arXiv, 2014-06-13)
This paper addresses the problem of semantic part parsing (segmentation) of cars, i.e.assigning every pixel within the car to one of the parts (e.g.body, window, lights, license plates and wheels). We formulate this as a ...