Results 261 to 270 of about 2,309 (295)

Localized Support Vector Machines for Classification

The 2006 IEEE International Joint Conference on Neural Network Proceedings, 2006
Support vector machines (SVMs) have been promising methods in pattern recognition because of their solid mathematical foundation. In this paper, we propose a localized SVM classification scheme (LSVM). In which we first cluster the training data in each category, and then train a set of SVMs based on these dusters. The SVMs trained from the clusters in
Ming Dong 0001, Jing Wu
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Fuzzy localization in machine-to-machine networks

2017
La localisation est un processus de base dans les réseaux Machine-to-Machine (M2M). Cette thèse présente une nouvelle approche pour la localisation des noeuds mobiles dans les réseaux M2M sans fil. Notre approche est basée sur la conception d'un système de localisation floue adaptatif. La première contribution proposée est de considérer les éléments de
Mathlouthi Baccar, Noura, Bouallegue, Ridha   +1 more
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Exploiting local structure in Boltzmann machines

Neurocomputing, 2011
Restricted Boltzmann machines (RBM) are well-studied generative models. For image data, however, standard RBMs are suboptimal, since they do not exploit the local nature of image statistics. We modify RBMs to focus on local structure by restricting visible-hidden interactions.
Hannes Schulz, Andreas C. Müller 0001, Sven Behnke   +2 more
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Locally linear support vector machines and other local models

The 2010 International Joint Conference on Neural Networks (IJCNN), 2010
The paper introduces various local models for solving machine learning (i.e., data mining) problems. In particular (and, due to their superior results) it focuses on a novel design of locally linear support vector machines classifiers. It presents them as powerful alternatives to the global (over the whole input space) nonlinear classifiers.
Vojislav Kecman, J. Paul Brooks
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Evaluation of localization systems for CNC machining of large FRPC parts [PDF]

Procedia CIRP, 2019
In machining of large fiber-reinforced polymer composite (FRPC) parts, the part must be precisely located before machining. The exact location and geometry are usually determined by the probing systems employing a touch probe integrated with a CNC ...
Selak, Luka, Bračun, Drago
exaly   +3 more sources

Machine Learning Based Localization Techniques

Advances in Artificial Intelligence and Machine Learning
Internet of Things (IoT) is growing at a pace that can be called ubiquitous. IoTs can be nominated as a subfield of a superset known as Wireless Sensor Networks (WSNs). These sensors are used for remote monitoring, target tracking, efficient transportation, industrial monitoring, patient observation through physiological sensors, smart agriculture ...
Aamir Zeb Shaikh, Shakil Ahmed, Kiran Hidayat, Minaal Ali, Abdul Rahim, Yamna Iqbal   +5 more
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Indoor Localization using Machine Learning and Beacons

2020 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan), 2020
In this paper, we use beacons and machine learning to localize indoor positions. The data used for machine learning consists of the RSSI value received by smartphones with eight beacons and the numerical code value, which means 13 indoor zones. K-Nearest Neighbors algorithm is used for model training.
Jae Yong Lee, Sang-Uk Park 0002, Myeong-in Choi, Guwon Yoon, Sehyun Park   +4 more
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Locality optimizations for parallel machines

1994
This paper focuses on the problem of locality optimizations for high-performance uniprocessor and multiprocessor systems. It shows that the problems of minimizing interprocessor communication and optimizing cache locality can be formulated in a similar manner.
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Fast and Scalable Local Kernel Machines.

J. Mach. Learn. Res., 2010
A computationally efficient approach to local learning with kernel methods is presented. The Fast Local Kernel Support VectorMachine (FaLK-SVM) trains a set of local SVMs on redundant neighbourhoods in the training set and an appropriate model for each query point is selected at testing time according to a proximity strategy.
Segata, Nicola, Blanzieri, Enrico
openaire   +2 more sources

Localized Video Compression for Machine Vision

2001
A three-dimensional vector quantization system is introduced suitable for video compression. The basic characteristics of slow or repeated scenes in robot vision are used as the basic assumptions of the proposed approach. Accordingly, the localized history of the sequence is used to create localized codebooks, thus representing current visual ...
openaire   +1 more source