Greedy Learning of Multiple Objects in Images Using Robust Statistics and Factorial Learning
نویسندگان
چکیده
منابع مشابه
Greedy Learning of Multiple Objects in Images Using Robust Statistics and Factorial Learning
We consider data that are images containing views of multiple objects. Our task is to learn about each of the objects present in the images. This task can be approached as a factorial learning problem, where each image must be explained by instantiating a model for each of the objects present with the correct instantiation parameters. A major problem with learning a factorial model is that as t...
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We consider data which are images containing views of multiple objects. Our task is to learn about each of the objects present in the images. This task can be approached as a factorial learning problem, where each image must be explained by instantiating a model for each of the objects present with the correct instantiation parameters. A major problem with learning a factorial model is that as ...
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Developing computer vision algorithms able to learn from unsegmented images containing multiple objects is important since this is how humans constantly learn from visual experiences. In this thesis we consider images containing views of multiple objects and our task is to learn about each of the objects present in the images. This task can be approached as a factorial learning problem, where e...
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ژورنال
عنوان ژورنال: Neural Computation
سال: 2004
ISSN: 0899-7667,1530-888X
DOI: 10.1162/089976604773135096