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An Optimized Intrusion Detection System Using PCA and BNN [PDF]
6th Asia-Pacific Symposium on Information and Telecommunication Technologies, 2005 This paper proposes an optimized Intrusion Detection System (IDS) using Principle Component Analysis (PCA) and Back-propagation Neural Network (BNN). Existing neural network based IDS are mainly suffering from two problems: one is to determine the numbers of hidden layers and regulating weight values to configure its topology.
Kim, Dong Seong +3 more
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Proceedings of the 30th ACM International Conference on Information & Knowledge Management, 2021
Deep learning (DL) algorithms have played a major role in achieving state-of-the-art (SOTA) performance in various learning applications, including computer vision, natural language processing, and recommendation systems (RSs). However, these methods are based on a vast amount of data and do not perform as well when there is a limited amount of data ...
Amit Livne +3 more
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Deep learning (DL) algorithms have played a major role in achieving state-of-the-art (SOTA) performance in various learning applications, including computer vision, natural language processing, and recommendation systems (RSs). However, these methods are based on a vast amount of data and do not perform as well when there is a limited amount of data ...
Amit Livne +3 more
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Journal of Catalysis, 2021
Abstract Porous hexagonal boron nitride nanosheets (p-BNNS) have demonstrated advantages in hydrogen storage, water purification and catalyst support. Boron nitride (BN) is generally considered chemically inert, but functionalized h-BN by physical or chemical methods breed new properties and applications and can catalyze some reactions. Herein, we
Qiong Lu +7 more
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Abstract Porous hexagonal boron nitride nanosheets (p-BNNS) have demonstrated advantages in hydrogen storage, water purification and catalyst support. Boron nitride (BN) is generally considered chemically inert, but functionalized h-BN by physical or chemical methods breed new properties and applications and can catalyze some reactions. Herein, we
Qiong Lu +7 more
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Physically Tightly Coupled, Logically Loosely Coupled, Near-Memory BNN Accelerator (PTLL-BNN)
ESSCIRC 2019 - IEEE 45th European Solid State Circuits Conference (ESSCIRC), 2019In this paper, a physically tightly coupled, logically loosely coupled, near-memory binary neural network accelerator (PTLL-BNN) is designed and fabricated. Both architecture-level and circuit-level optimizations are presented. From the perspective of processor architecture, the PTLL-BNN includes two new design choices.
Yun-Chen Lo +7 more
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SA-BNN: State-Aware Binary Neural Network
Proceedings of the AAAI Conference on Artificial Intelligence, 2021Binary Neural Networks (BNNs) have received significant attention due to the memory and computation efficiency recently. However, the considerable accuracy gap between BNNs and their full-precision counterparts hinders BNNs to be deployed to resource-constrained platforms.
Chunlei Liu 0001 +5 more
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Journal of Materials Science: Materials in Electronics, 2018
It is still challenging in obtaining an insulation material with high thermal conductivity and excellent mechanical properties, while suppressing the distribution of space charges. In this article, exfoliated hexagonal boron nitride nanosheets (BNNS) were introduced into low-density polyethylene (LDPE) to optimize the electrical, thermal and mechanical
Jialong Li +9 more
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It is still challenging in obtaining an insulation material with high thermal conductivity and excellent mechanical properties, while suppressing the distribution of space charges. In this article, exfoliated hexagonal boron nitride nanosheets (BNNS) were introduced into low-density polyethylene (LDPE) to optimize the electrical, thermal and mechanical
Jialong Li +9 more
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Strategic Partnership Looks to Drive BNNs
New Electronics, 2020XMOS AND PLUMERAI PARTNER TO ACCELERATE BINARISED NEURAL NETWORKS.
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Image recovery by D-SET framework with improved BNN
2015 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS), 2015Decomposed SET, namely Smooth, Edge, and Texture, (D-SET) recovery, is an image decomposition and recovery method which assumes images as the sum of smooth, edge, and texture components. All the components are obtained by solving an optimization problem consists of regularizations based on priori information of original images.
Teruaki Fujiyoshi +2 more
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2022 IEEE 24th Electronics Packaging Technology Conference (EPTC), 2022
Jinming Li +3 more
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Jinming Li +3 more
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Instability in the cobweb model under the BNN dynamic
Journal of Mathematical Economics, 2010zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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