Results 111 to 120 of about 6,478,030 (244)

Emerging Post‐CMOS Hardware Neurons for Brain‐Inspired Computing: Devices, Circuits, and System Integration

Advanced Functional Materials, EarlyView.
The physical realization of artificial neurons is a critical challenge for energy‐efficient neuromorphic computing. This review presents a comprehensive analysis of the evolution of artificial neuron implementations from conventional CMOS to emerging post‐CMOS technologies.
Kannan Udaya Mohanan, Hocheon Yoo, Benoît H. Lessard, Ioannis Kymissis, Chang‐Hyun Kim   +4 more
wiley   +1 more source

A neural network for counter-terrorism [PDF]

, 2011
This article presents findings concerned with the use of neural networks in the identification of deceptive behaviour. A game designed by psychologists and criminologists was used for the generation of data used to test the appropriateness of different ...
M.B. Dixon, J. Elliott, Dixon, S. J., E. Guest, S.J. Dixon, D. J. Mullier, Elliott, J, Mullier, DJ, Dixon, M. B., Mullier, D. J., Elliott, J., Guest, E, Dixon, MB, Guest, E., Dixon, SJ, Elliott, J.; id_orcid   +15 more
core   +1 more source

Multiprocessing neural network simulator

, 2013
Over the last few years tremendous progress has been made in neuroscience by employing simulation tools for investigating neural network behaviour.
Kulakov, Anton
core   +1 more source

Machine Learning-Based Analysis of Travel Mode Preferences: Neural and Boosting Model Comparison Using Stated Preference Data from Thailand’s Emerging High-Speed Rail Network

Big Data and Cognitive Computing
This study examines travel mode choice behavior within the context of Thailand’s emerging high-speed rail (HSR) development. It conducts a comparative assessment of predictive capabilities between the conventional Multinomial Logit (MNL) framework and ...
Chinnakrit Banyong, Natthaporn Hantanong, Supanida Nanthawong, Chamroeun Se, Panuwat Wisutwattanasak, Thanapong Champahom, Vatanavongs Ratanavaraha, Sajjakaj Jomnonkwao   +7 more
doaj   +1 more source

A New Robust Deep Canonical Correlation Analysis Algorithm for Small Sample Problems

IEEE Access, 2019
As a nonlinear feature learning method, deep canonical correlation analysis (DCCA) has got a great success in computer vision. Compared with kernel methods, deep neural networks can more easily process large amounts of training data and do not require ...
Yan Liu, Yun Li, Yun-Hao Yuan, Hui Zhang
doaj   +1 more source

Investigating on Gradient Regularization for Testing Neural Networks

Convolutional Neural Networks (CNNs) have become ubiquitous in diverse applications, including safety-critical domains such as autonomous driving, where ensuring reliability is crucial. CNNs reliability can be jeopardized by the occurrence of hardware faults during the inference, leading to severe consequences.
Nicolò Bellarmino, Alberto Bosio, Riccardo Cantoro, Annachiara Ruospo, Ernesto Sánchez 0001, Giovanni Squillero   +5 more
openaire   +1 more source

Bio‐Inspired Artificial Ionic Mechanoreceptor

Advanced Functional Materials, EarlyView.
A skin‐inspired artificial mechanoreceptor based on ionic interactions is presented for biomimetic tactile sensing. Pressure‐driven ionic redistribution within microfluidic channels generates a self‐powered electrical signal without external bias. The generated waveform exhibits mechanoreceptor‐like temporal features, including overshoot and undershoot,
Mohammad Akbari, Jeppe Don, Lasse A. N. Pedersen, John Noee, Rassoul Tabassian   +4 more
wiley   +1 more source

Controller Application of a Multi-Layer Quantum Neural Network with Qubit Neurons

Journal of Advanced Mechanical Design, Systems, and Manufacturing, 2012
This paper investigates a quantum neural network and discusses its application in control systems. A learning-type neural network-based controller that uses a multi-layer quantum neural network having qubit neurons as its information processing unit is ...
Kazuhiko TAKAHASHI, Motoki KUROKAWA, Masafumi HASHIMOTO   +2 more
doaj   +1 more source

Reservoir‐Driven Neuromorphic Computing Based on Composite Rare‐Earth/Transition Metal Oxide Memristor

Advanced Functional Materials, EarlyView.
A defect‐engineered Ag/Gd2O3:Nb2O5/Pt rare earth composite oxide memristor enables stable multilevel reservoir states through pulse driven conductance modulation. Experimentally measured device responses are incorporated into a device aware reservoir computing framework for CIFAR‐100 image classification, highlighting the potential of rare earth ...
Hammad Ghazanfar, Haider Abbas, Muhammad Rabeel, Honggyun Kim, Ghulam Dastgeer, Muhammad Nasim, Furqan Zahoor, Yawar Abbas, Waqas Ahmad, Deok‐kee Kim   +9 more
wiley   +1 more source

An Adaptive Inhibitory WSe2 Transistor for Retinomorphic In‐Sensor Image Processing

Advanced Functional Materials, EarlyView.
Conventional retinomorphic devices typically require deliberate gate‐bias tuning for each illumination condition. In this paper, we demonstrate an adaptive inhibitory WSe2 transistor that uses photo‐induced regime shift between the subthreshold and accumulation modes to achieve decision‐free, intensity‐adaptive image processing within a single pixel ...
Juhwan Baek, Junhwa Oh, Hyeonjung Kim, Minsik Park, Haein Cho, Jin Young Park, Hyeonchang Son, Taeyun Kim, Sung‐Un An, Yamin Zhang, Hyeon‐Jin Shin, Seyong Oh, Dong‐Ho Kang   +12 more
wiley   +1 more source