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» Variability in Automation System Models
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CVPR
2009
IEEE
16 years 9 months ago
What's It Going to Cost You?: Predicting Effort vs. Informativeness for Multi-Label Image Annotations
Active learning strategies can be useful when manual labeling effort is scarce, as they select the most informative examples to be annotated first. However, for visual category ...
Sudheendra Vijayanarasimhan (University of Texas a...
ICCAD
2005
IEEE
176views Hardware» more  ICCAD 2005»
15 years 11 months ago
Statistical gate sizing for timing yield optimization
— Variability in the chip design process has been relatively increasing with technology scaling to smaller dimensions. Using worst case analysis for circuit optimization severely...
Debjit Sinha, Narendra V. Shenoy, Hai Zhou
CSB
2005
IEEE
145views Bioinformatics» more  CSB 2005»
15 years 8 months ago
Classification Methods for HIV-1 Medicated Neuronal Damage
HIV-1-associated dementia (HAD) is the most devastating disease happened in the central nervous system of AIDS patients. Neuronal damage, the early indicator of HAD, under differe...
Mengjun Wang, Jialin Zheng, Zhengxin Chen, Yong Sh...
FIRBPERF
2005
IEEE
259views Algorithms» more  FIRBPERF 2005»
15 years 8 months ago
Performance Issues in Video Streaming Environments
The main motivation for applying capacity planning techniques to the design of Internet-based video services is that very often these systems incur significant delays that decrea...
Giuliano Casale, Paolo Cremonesi, Giuseppe Serazzi...
ICRA
2005
IEEE
105views Robotics» more  ICRA 2005»
15 years 8 months ago
A New Approach to the Use of Edge Extremities for Model-based Object Tracking
— This paper presents a robust model-based visual tracking algorithm that can give accurate 3D pose of a rigid object. Our tracking algorithm uses an incremental pose update sche...
Youngrock Yoon, Akio Kosaka, Jae Byung Park, Avina...