Jennifer Louie

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© 2 0 0 3 m a s s a c h u s e t t s i n s t i t u t e o f t e c h n o l o g y, c a m b r i d g e , m a 0 2 1 3 9 u s a — w w w. a i. m i t. e d u Abstract Previous biological models of object recognition in cortex have been evaluated using idealized scenes and have hard-coded features, such as the HMAX model by Riesenhuber and Poggio [10]. Because HMAX uses(More)
Models of object recognition in cortex have so far been mostly applied to tasks involving the recognition of isolated objects presented on blank backgrounds. However, ultimately models of the visual system have to prove themselves in real world object recognition tasks. Here we took a first step in this direction: We investigated the performance of the hmax(More)
Automatic indexing of large collections of multimedia data is important for enabling retrieval functions. Current approaches mostly draw on a single or dual modality of video content analysis. Here we describe a framework for the integration of multimedia content and context information, which generalizes and systematizes current methods. Content(More)
BACKGROUND Pembrolizumab is a monoclonal antibody that is designed against programmed cell death protein 1 (PD-1). Pembrolizumab and other immunocheckpoint-blocking monoclonal antibodies work by modulating a patient's own immune system to increase anti-tumor activity. While immunocheckpoint blockade has shown promising results, only 20-40 % of patients(More)
The Problem: To evaluate a biological model of object recognition that uses feature learning to distinguish between classes of objects. Motivation: On the computational neuroscience side, applying a biologically plausible model of object recognition to a real world task, namely face detection, tests out whether the concepts behind the model hold. Current(More)
The Problem: We propose a biologically plausible model of object recognition in cortex that handles a real-world face detection task at the level of state-of-the-art machine vision systems. Motivation: Models of object recognition in cortex have been mostly applied to tasks involving the recognition of isolated objects presented on blank backgrounds.(More)
Previous biological models of object recognition in cortex have been evaluated using idealized scenes and have hard-coded features, such as the HMAX model by Riesen-huber and Poggio [10]. Because HMAX uses the same set of features for all object classes, it does not perform well in the task of detecting a target object in clutter. This thesis presents a new(More)
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