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A Free Lunch From ANN: Towards Efficient, Accurate Spiking Neural Networks Calibration [article]

Yuhang Li, Shikuang Deng, Xin Dong, Ruihao Gong, Shi Gu
2021 arXiv   pre-print
Spiking Neural Network (SNN) has been recognized as one of the next generation of neural networks.  ...  We introduce SNN Calibration, a cheap but extraordinarily effective method by leveraging the knowledge within a pre-trained Artificial Neural Network (ANN).  ...  Introduction Spiking neural networks (SNNs) are based on the spiking neural behavior in biological neurons (Hodgkin & Huxley, 1952; Izhikevich, 2003) .  ... 
arXiv:2106.06984v1 fatcat:2xn3nps3jvgwjjblgfbvekue3i

EMG-based Simultaneous and Proportional Estimation of Wrist Kinematics and its Application in Intuitive Myoelectric Control for Unilateral transradial Amputees

Farina Dario
2011 Frontiers in Computational Neuroscience  
[T 10] Inferring intrinsic saliency from free-viewing data Simon Barthelme 1* , Hans Trukenbrod 2 , Ralf Engbert 2 and Felix A.  ...  Neural Networks 21, 1070-1075. Acknowledgements We thank M. Kaczorowski for her assistance with the histological procedures.  ...  We propose a new, binning-free application of the GLM framework to model neural activity by noting that spike trains can equally be characterized by the sequence of continuous-valued inter-spike intervals  ... 
doi:10.3389/conf.fncom.2011.53.00081 fatcat:nkq5wesfpbcjnikbxqh3v3gtqi

Deep Learning in Mobile and Wireless Networking: A Survey

Chaoyun Zhang, Paul Patras, Hamed Haddadi
2019 IEEE Communications Surveys and Tutorials  
In this paper we bridge the gap between deep learning and mobile and wireless networking research, by presenting a comprehensive survey of the crossovers between the two areas.  ...  We then discuss several techniques and platforms that facilitate the efficient deployment of deep learning onto mobile systems.  ...  This opens a new research direction toward embedding machine learning towards greening cellular networks. C.  ... 
doi:10.1109/comst.2019.2904897 fatcat:xmmrndjbsfdetpa5ef5e3v4xda

Deep Learning in Mobile and Wireless Networking: A Survey [article]

Chaoyun Zhang, Paul Patras, Hamed Haddadi
2019 arXiv   pre-print
In this paper we bridge the gap between deep learning and mobile and wireless networking research, by presenting a comprehensive survey of the crossovers between the two areas.  ...  We then discuss several techniques and platforms that facilitate the efficient deployment of deep learning onto mobile systems.  ...  This opens a new research direction toward embedding machine learning towards greening cellular networks. C.  ... 
arXiv:1803.04311v3 fatcat:awuvyviarvbr5kd5ilqndpfsde

Program

2021 2021 IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)  
However, it has been heavily debated whether artificial neural networks (ANNs) or recurrent neural networks (RNNs) are the most appropriate for sales forecasting.  ...  network algorithm in a free space optical (FSO) channel.  ... 
doi:10.1109/icce-tw52618.2021.9602919 fatcat:aetmvxb7hfah7iuucbamos2wgu

Program

2020 2020 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)  
Finally, we refine more accurate tampered areas through a refined segmentation network.  ...  This paper presents an end-to-end rapid prototyping methodology that performs automated and efficient mapping of desired neural networks onto FPGA.  ...  A convolution neural network (CNN) was built to efficiently map the subject's emotions with the extracted features from both ECG and PPG signals.  ... 
doi:10.1109/icce-taiwan49838.2020.9258230 fatcat:g25vw7mzvradxna2grlzp6kgiq

A Complete Proposed Framework for Coastal Water Quality Monitoring System with Algae Predictive Model

N. A. P. Rostam, N. H. A. H. Malim, R. Abdullah, A. L. Ahmad, B. S. Ooi, D. J. C. Chan
2021 IEEE Access  
through the prediction of chlorophyll-a (Chl-a) as a strong indicator of algal presence for coastal studies.  ...  Among all the algorithms selected, Long Short-term Memory (LSTM) is the best fit for the prediction method and has outperformed other basic machine learning methods in accurately predicting algal growth  ...  Moreover, in machine learning itself, the No Free Lunch Theorems [75] indicated that a general-purpose, common strategy is unfeasible.  ... 
doi:10.1109/access.2021.3102044 fatcat:c7pint6ddrdgrgijh6ie3zgara

Multi-period portfolio selection with drawdown control

Peter Nystrup, Stephen Boyd, Erik Lindström, Henrik Madsen
2018 Annals of Operations Research  
As a benchmark, also forecasts from an artificial neural network autoregression (NNAR), ARIMA and ETS model are produced.  ...  In this paper a particular type of downstream data, EDI 852 product activity data, is employed in producing short-term weekly demand forecasts obtained from an ARIMAX, ETS-X, artificial neural network  ...  We discuss the obtained results from the business perspective covering forecasts applications in the inventory optimization and demand planning areas.  ... 
doi:10.1007/s10479-018-2947-3 fatcat:haworusnrfcqvlmkmbidfwb5wu

Optical aspects of a miniature fluorescence microscope for super-sensitive biomedical detection

Yunfeng Nie, Aikio Sanna, Annukka Kokkonen, Teemu Sipola, Uusitalo Sanna, Simonetta Grilli, Heidi Ottevaere
2020 Zenodo  
We present optical design and the principle demonstrator of a miniature fluorescence microscope aiming for super-sensitive detection.  ...  An improved method for the optical readout of voltage indicators is presented, whereby fluorescence from the whole surface of a neuron is integrated onto a single detector, dramatically increasing the  ...  JTh2A.33 Mapping neural correlates to language and biological motion in school-age children with autism using high-density diffuse optical tomography, Alexandra M.  ... 
doi:10.5281/zenodo.3822435 fatcat:3eoome22a5grbmarbrktphfh7a

Assessing the impact of machine intelligence on human behaviour: an interdisciplinary endeavour [article]

Emilia Gómez, Carlos Castillo, Vicky Charisi, Verónica Dahl, Gustavo Deco, Blagoj Delipetrev, Nicole Dewandre, Miguel Ángel González-Ballester, Fabien Gouyon, José Hernández-Orallo, Perfecto Herrera, Anders Jonsson, Ansgar Koene (+11 others)
2018 arXiv   pre-print
In the conclusion section, we provide a list of emerging research topics and strategies to be addressed in the near future.  ...  The workshop was organized in the context of a new research programme at the Centre for Advanced Studies, Joint Research Centre of the European Commission, which focuses on studying the potential impact  ...  Authors (editor plus authors in alphabetical order) Emilia Gómez ( The investigation of how children interact with machines is a virtually unexplored field.  ... 
arXiv:1806.03192v1 fatcat:jypjtwtgxbg5vbkigudnxtsp64

MyShake: Using Human-Centered Design Methods to Promote Engagement in a Smartphone-Based Global Seismic Network

Kaylin Rochford, Jennifer A. Strauss, Qingkai Kong, Richard M. Allen
2018 Frontiers in Earth Science  
It is powered by the participation of users, therefore, its success as a global network and its utility for the users themselves is reliant on their engagement and continued involvement.  ...  resource to a wider range of users in earthquake-prone regions.  ...  An on-board patented artificial neural network (ANN) created by the researchers at the Berkeley Seismology Lab determines whether or not recorded motions are produced by an earthquake or by normal human  ... 
doi:10.3389/feart.2018.00237 fatcat:tl53l62wrzhk5ewudgtz4tsvam

Learning and Memory [chapter]

Richard F. Thompson, Nelson H. Donegan
1989 Learning and Memory  
Magnetic resonance image (MRI) scan of a parasagittal section from the left side of H.M.'s brain. The calibration bar on the right side of the panel has 1 cm increments.  ...  As we have emphasized throughout this book, neural science and cognitive psychology have now found a common ground, and we are beginning to benefit from the increased explanatory power that results from  ...  This work was supported by grants from the National Institute of Mental Health.  ... 
doi:10.1007/978-1-4899-6778-7_2 fatcat:x73uwhvvx5btffnrkhafwc3cna

A Note on Several Meteorological Topics Related to Polar Regions [article]

Krzysztof Sienicki
2011 arXiv   pre-print
The nature of air circulation in a polar vortex is of preliminary importance.  ...  On a continental scale, the wind events in the Antarctic tend to be self-organized criticality with ergodic properties.  ...  Acknowledgements I wish to thank Professor Leszek Kułak from the Department of Theoretical Physics and Quantum Informatics at the Technical University of Gdańsk, Poland for assistance with neural network  ... 
arXiv:1108.3781v1 fatcat:ibvnuhizvrhfjaxrxtkdoupbhm

The "Catalyst to Better Diabetes Care Act of 2007"

David C. Klonoff
2008 Journal of Diabetes Science and Technology  
We demonstrate that beads coated with such a device can release several pulses of insulin when triggered by a small molecule drug.  ...  Examples of our substantial improvements include a reduction of "outof-control" days by 60% (p < 0.001), a mean surgical intensive care unit BG reduction of 15 mg/dl (p < 0.001), and a system reduction  ...  Artificial neural networks modeling and identifying patients through clinical data monitoring therefore are not necessary.  ... 
doi:10.1177/193229680800200201 pmid:19885363 pmcid:PMC2771484 fatcat:htkqbeadrfbfzfynzvzp2k4dyi

Cost-to-Go Function Approximation [chapter]

2017 Encyclopedia of Machine Learning and Data Mining  
It maintains a set, S , of most specific hypotheses that are consistent with the training data and a set, G, of most general hypotheses consistent with the training data.  ...  Mitchell's, (1982; candidate-elimination algorithm performs a bidirectional search in the hypothesis space.  ...  In this case, the resulting theory is interpreted as a decision list. In the following, we will assume a two-class problem with a positive and a negative class.  ... 
doi:10.1007/978-1-4899-7687-1_100093 fatcat:vse7ncdqs5atlosjhz7fhlj3im
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