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» Efficient, Simultaneous Detection of Multiple Object Classes
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ICDM
2010
IEEE
199views Data Mining» more  ICDM 2010»
13 years 5 months ago
Addressing Concept-Evolution in Concept-Drifting Data Streams
Abstract--The problem of data stream classification is challenging because of many practical aspects associated with efficient processing and temporal behavior of the stream. Two s...
Mohammad M. Masud, Qing Chen, Latifur Khan, Charu ...
ICCV
2009
IEEE
13 years 5 months ago
Incremental Multiple Kernel Learning for object recognition
A good training dataset, representative of the test images expected in a given application, is critical for ensuring good performance of a visual categorization system. Obtaining ...
Aniruddha Kembhavi, Behjat Siddiquie, Roland Miezi...
DICTA
2008
13 years 9 months ago
Exploiting Part-Based Models and Edge Boundaries for Object Detection
This paper explores how to exploit shape information to perform object class recognition. We use a sparse partbased model to describe object categories defined by shape. The spars...
Josephine Sullivan, Oscar M. Danielsson, Stefan Ca...
CAAN
2004
Springer
14 years 1 months ago
Bandwidth Allocation in Networks: A Single Dual Update Subroutine for Multiple Objectives
We study the bandwidth allocation problem Maximize U(x), subject to Ax ≤ c; x ≥ 0 where U is a utility function, x is a bandwidth allocation vector, and Ax ≤ c represent the...
Sung-woo Cho, Ashish Goel
ICIP
2010
IEEE
13 years 5 months ago
Fast object detection using boosted co-occurrence histograms of oriented gradients
Co-occurrence histograms of oriented gradients (CoHOG) are powerful descriptors in object detection. In this paper, we propose to utilize a very large pool of CoHOG features with ...
Haoyu Ren, Cher-Keng Heng, Wei Zheng, Luhong Liang...