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Results 21 - 30
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804
Part and Appearance Sharing: Recursive Compositional Models for Multi-View Multi-Object Detection
, 2010
"... We propose Recursive Compositional Models (RCMs) for simultaneous multi-view multi-object detection and parsing (e.g. view estimation and determining the positions of the object subparts). We represent the set of objects by a family of RCMs where each RCM is a probability distribution defined over a ..."
Abstract
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Cited by 24 (5 self)
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for the set of objects and which enables efficient inference and learning from a limited number of training samples. In addition, we use appearance-sharing so that RCMs for the same object, but different viewpoints, share similar appearance cues which also helps efficient learning. RCMs lead to a multi
Behavioral theories and the neurophysiology of reward,
- Annu. Rev. Psychol.
, 2006
"... ■ Abstract The functions of rewards are based primarily on their effects on behavior and are less directly governed by the physics and chemistry of input events as in sensory systems. Therefore, the investigation of neural mechanisms underlying reward functions requires behavioral theories that can ..."
Abstract
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Cited by 187 (0 self)
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that can conceptualize the different effects of rewards on behavior. Thus, the exploration of neural reward mechanisms should not be based primarily on the physics and chemistry of reward objects but on specific behavioral theories that define reward functions. Animal learning theory and microeconomics
Learning an Alphabet of Shape and Appearance for Multi-Class Object Detection
- INT J COMPUT VIS
, 2008
"... We present a novel algorithmic approach to object categorization and detection that can learn category specific detectors, using Boosting, from a visual alphabet of shape and appearance. The alphabet itself is learnt incrementally during this process. The resulting representation consists of a set ..."
Abstract
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Cited by 47 (0 self)
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We present a novel algorithmic approach to object categorization and detection that can learn category specific detectors, using Boosting, from a visual alphabet of shape and appearance. The alphabet itself is learnt incrementally during this process. The resulting representation consists of a
OBJECT SHARING IN MULTI-FUNCTION
"... Smart cards, Chip cards, and Integrated Circuit(s) Cards (ICC) were invented and patented in the 70s. A smart card is embedded with either a microprocessor and a memory chip or simply a memory chip with non-programmable logic. Today, there are three broad categories of smart cards: Microprocessor Ca ..."
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Cards, Memory Cards, and Optical Memory Cards. In the 90s, the smart card prevailed, specifically, with the introduction of the smart-card-based Subscriber Identity Module (SIM) used in the Global System for Mobile Communications (GSM) mobile phone equipment in Europe. Since then smart cards proven
Multi-objective Machine Learning Application: Fuzzy Tuning for the Docking Maneuver Controller of an Automated Guided Vehicle
"... In some environments, mobile robots need to perform tasks in a precise manner. For this reason, we require obtaining good controllers in charge of these control tasks. In this work, we present a real-world application in the domain of multi-objective machine learning, which consists of an Automated ..."
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based on a multi-objective evolutionary algorithm in order to find multiple fuzzy logic controllers which optimize specific objectives and satisfy imposed constraints for docking task in charge of following up an online generated trajectory. 1
Adaptive Selection of Helper-Objectives with Reinforcement Learning
"... Abstract-In this paper a previously proposed method of choosing auxiliary fitness functions is applied to adaptive selection of helper-objectives. Helper-objectives are used in evolutionary computation to enhance the optimization of the primary objective. The method based on choosing between object ..."
Abstract
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Cited by 1 (1 self)
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. It is also shown that the proposed method outperforms multi-objective evolutionary algorithms, that were used with helper-objectives originally.
Learning CRFs using Graph Cuts
"... Abstract. Many computer vision problems are naturally formulated as random fields, specifically MRFs or CRFs. The introduction of graph cuts has enabled efficient and optimal inference in associative random fields, greatly advancing applications such as segmentation, stereo reconstruction and many o ..."
Abstract
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Cited by 104 (8 self)
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values under standard regularized objective functions that ensure good generalization. Our algorithm enables learning of many parameters in reasonable time, and we explore further speedup techniques. We also discuss extensions to non-associative and multi-class problems. We evaluate the method on image
MULTI-OBJECTIVE OPTIMIZATION OF LAMINATED COMPOSITE PLATE USING A NON-DOMINATED SORTING GENETIC ALGORITHM
"... Laminated composite constructions of panels and other structural elements are currently being used for many applications in aerospace, automotive, civil and defence industries. Laminated composites have general advantages over more traditional materials such as greater specific strength, specific st ..."
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pareto-optimal design of composite laminate square plate. The objectives are to minimize the weight and deflection of graphite/epoxy square plate subjected to the constraint that the Tsai-Wu failure factor (ζ) should be less than or equal to one. The multi-objective optimization algorithm used
A Multi-Objective Genetic Algorithm for Learning Linguistic Persistent Queries in Text Retrieval Environments
, 2006
"... Persistent queries are a specific kind of queries used in information retrieval systems to represent a user’s long-term standing information need. These queries can present many different structures, being the “bag of words” that most commonly used. They can be sometimes formulated by the user, alth ..."
Abstract
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Cited by 1 (0 self)
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Persistent queries are a specific kind of queries used in information retrieval systems to represent a user’s long-term standing information need. These queries can present many different structures, being the “bag of words” that most commonly used. They can be sometimes formulated by the user
Software Module Clustering using a Fast Multi-objective Hyper-heuristic Evolutionary Algorithm
"... Software evolution is a natural phenomenon in the software development life cycle. As the software evolves, the modular structure of software degrades, and at one point it becomes a challenging task to maintain the software further. Software module clustering is an important activity during software ..."
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Problem with multiple objectives. This problem is NP hard as it is an instance of graph partitioning and hence cannot be solved using traditional optimization techniques. The Multiobjective Hyper-heuristic Evolutionary Algorithm (MHypEA) is a fast and effective metaheuristic search technique
Results 21 - 30
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804
