Many tracking systems are based on the Global Positioning System (GPS), Global System for Mobile communications (GSM) and smart phones, due to their wide availability and reliability. A moving object to be tracked, it...
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An advanced Fuzzy Logic controller (FLC) that considers all the states of the brain tumor system is designed for the chemotherapy treatment. A Mamdani-type FLC is proposed for dynamically controlling the chemotherapy ...
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The paper presents constraint satisfaction problem driven approach to analytical solution of the cyclic scheduling problem in the Flexible Manufacturing System (FMS) producing multi-type parts where for material handl...
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Since Convolutional Neural Networks (CNNs) have become the leading learning paradigm in visual recognition, Naive Bayes Nearest Neighbor (NBNN)-based classifiers have lost momentum in the community. This is because (1...
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ISBN:
(纸本)9781467388511
Since Convolutional Neural Networks (CNNs) have become the leading learning paradigm in visual recognition, Naive Bayes Nearest Neighbor (NBNN)-based classifiers have lost momentum in the community. This is because (1) such algorithms cannot use CNN activations as input features; (2) they cannot be used as final layer of CNN architectures for end-to-end training, and (3) they are generally not scalable and hence cannot handle big data. This paper proposes a framework that addresses all these issues, thus bringing back NBNNs on the map. We solve the first by extracting CNN activations from local patches at multiple scale levels, similarly to [13]. We address simultaneously the second and third by proposing a scalable version of Naive Bayes Non-linear Learning (NBNL, [7]). Results obtained using pre-trained CNNs on standard scene and domain adaptation databases show the strength of our approach, opening a new season for NBNNs.
Although they have been known for some time, the security implications of buffer overflows (BOF) continue to rouse great attention among software experts in the academic and commercial sectors. Recently, there has bee...
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We extend the prepare-and-measure frequency-time coding quantum key distribution (FT-QKD) protocol to an entanglement based FT-QKD protocol. The latter can be implemented with a correlated frequency measurement scheme...
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In this article, implementation of a self-learning fuzzy logic controller (SLFLC) in a form of PLC super block is described. The SLFLC contains a learning algorithm that utilizes a second-order reference model and a s...
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The cellular neural network (CNN) is a powerful technique to mimic the local function of biological neural circuits for real-time image and video processing. Recently, it is widely accepted that using a set of CNNs in...
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In this paper, a communication load balanced dynamic topology management algorithm (CLB-AODV) is proposed to extend the wireless sensor network (WSN) lifetime via managing the participation in communication process am...
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Gait phase recognition systems are widely used in medicine to control devices aimed at restoration of patients’ motor functions and have an increasing interest in scientific society. Use of electromyography as a sour...
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