Caltech 101

Caltech 101 is a data set of digital images created in September 2003 and compiled by Fei-Fei Li, Marco Andreetto, Marc 'Aurelio Ranzato and Pietro… (More)
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2016
2016
Abstrak— Deep Learning adalah sebuah bidang keilmuan baru dalam bidang Machine Learning yang akhir-akhir ini berkembang karena… (More)
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2014
Highly Cited
2014
Large Convolutional Network models have recently demonstrated impressive classification performance on the ImageNet benchmark… (More)
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2011
Highly Cited
2011
Datasets are an integral part of contemporary object recognition research. They have been the chief reason for the considerable… (More)
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2010
Highly Cited
2010
Caltech-UCSD Birds 200 (CUB-200) is a challenging image dataset annotated with 200 bird species. It was created to enable the… (More)
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2010
2010
Visual object categorization is one of the most active research topics in computer vision, and Caltech-101 data set is one of the… (More)
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2009
Highly Cited
2009
In many recent object recognition systems, feature extraction stages are generally composed of a filter bank, a non-linear… (More)
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2008
Highly Cited
2008
State-of-the-art image classification methods require an intensive learning/training stage (using SVM, Boosting, etc.) In… (More)
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2007
Highly Cited
2007
The objective of this paper is classifying images by the object categories they contain, for example motorbikes or dolphins… (More)
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2006
Highly Cited
2006
This paper presents a method for recognizing scene categories based on approximate global geometric correspondence. This… (More)
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2005
Highly Cited
2005
We approach recognition in the framework of deformable shape matching, relying on a new algorithm for finding correspondences… (More)
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