Zobrazeno 1 - 10
of 159
pro vyhledávání: '"Breuel, Thomas M."'
We introduce an edge detection and recovery framework based on open active contour models (snakelets). This is motivated by the noisy or broken edges output by standard edge detection algorithms, like Canny. The idea is to utilize the local continuit
Externí odkaz:
http://arxiv.org/abs/1609.03415
In this paper, we extend a symbolic association framework for being able to handle missing elements in multimodal sequences. The general scope of the work is the symbolic associations of object-word mappings as it happens in language development in i
Externí odkaz:
http://arxiv.org/abs/1511.04401
Autor:
Breuel, Thomas M.
The paper introduces a biologically and evolutionarily plausible neural architecture that allows a single group of neurons, or an entire cortical pathway, to be dynamically reconfigured to perform multiple, potentially very different computations. Th
Externí odkaz:
http://arxiv.org/abs/1508.02792
Autor:
Breuel, Thomas M.
The performance of neural network classifiers is determined by a number of hyperparameters, including learning rate, batch size, and depth. A number of attempts have been made to explore these parameters in the literature, and at times, to develop me
Externí odkaz:
http://arxiv.org/abs/1508.02788
Autor:
Breuel, Thomas M.
Neural networks are usually trained by some form of stochastic gradient descent (SGD)). A number of strategies are in common use intended to improve SGD optimization, such as learning rate schedules, momentum, and batching. These are motivated by ide
Externí odkaz:
http://arxiv.org/abs/1508.02790
Autor:
Breuel, Thomas M.
LSTM (Long Short-Term Memory) recurrent neural networks have been highly successful in a number of application areas. This technical report describes the use of the MNIST and UW3 databases for benchmarking LSTM networks and explores the effect of dif
Externí odkaz:
http://arxiv.org/abs/1508.02774
Autor:
Breuel, Thomas M.
This thesis presents there important results in visual object recognition based on shape. (1) A new algorithm (RAST; Recognition by Adaptive Sudivisions of Tranformation space) is presented that has lower average-case complexity than any known recogn
Externí odkaz:
http://hdl.handle.net/1721.1/7342
Autor:
Breuel, Thomas M.
Learning object models from views in 3D visual object recognition is usually formulated either as a function approximation problem of a function describing the view-manifold of an object, or as that of learning a class-conditional density. This paper
Externí odkaz:
http://arxiv.org/abs/0712.0136
Autor:
Breuel, Thomas M.
For a classification problem described by the joint density $P(\omega,x)$, models of $P(\omega\eq\omega'|x,x')$ (the ``Bayesian similarity measure'') have been shown to be an optimal similarity measure for nearest neighbor classification. This paper
Externí odkaz:
http://arxiv.org/abs/0712.0130
Autor:
Breuel, Thomas M.
This paper proves that visual object recognition systems using only 2D Euclidean similarity measurements to compare object views against previously seen views can achieve the same recognition performance as observers having access to all coordinate i
Externí odkaz:
http://arxiv.org/abs/0712.0137