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» Object Recognition via Local Patch Labelling
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ICPR
2006
IEEE
14 years 8 months ago
Object Localization Using Input/Output Recursive Neural Networks
Localizing objects in images is a difficult task and represents the first step to the solution of the object recognition problem. This paper presents a novel approach to the local...
Lorenzo Sarti, Marco Maggini, Monica Bianchini
ICPR
2004
IEEE
14 years 8 months ago
Relaxation Labeling Processes for Protein Secondary Structure Prediction
The prediction of protein secondary structure is a classical problem in bioinformatics, and in the past few years several machine learning techniques have been proposed to t. From...
Giacomo Colle, Marcello Pelillo
PSIVT
2009
Springer
139views Multimedia» more  PSIVT 2009»
14 years 2 months ago
Recognizing Multiple Objects via Regression Incorporating the Co-occurrence of Categories
Abstract. Most previous methods for generic object recognition explicitly or implicitly assume that an image contains objects from a single category, although objects from multiple...
Takahiro Okabe, Yuhi Kondo, Kris M. Kitani, Yoichi...
ICCV
2005
IEEE
14 years 9 months ago
Creating Efficient Codebooks for Visual Recognition
Visual codebook based quantization of robust appearance descriptors extracted from local image patches is an effective means of capturing image statistics for texture analysis and...
Bill Triggs, Frédéric Jurie
CVPR
2012
IEEE
11 years 10 months ago
Discovering localized attributes for fine-grained recognition
Attributes are visual concepts that can be detected by machines, understood by humans, and shared across categories. They are particularly useful for fine-grained domains where c...
Kun Duan, Devi Parikh, David J. Crandall, Kristen ...