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Artykuły w czasopismach na temat "Binary output"
Anashin, Vladimir. "Discreteness causes waves". Facta universitatis - series: Physics, Chemistry and Technology 14, nr 3 (2016): 143–96. http://dx.doi.org/10.2298/fupct1603143a.
Pełny tekst źródłaMoreno, E. G., B. Iniguez, M. Roca, J. Segura i S. Sureda. "CMOS radiation sensor with binary output". IEEE Transactions on Nuclear Science 42, nr 3 (czerwiec 1995): 174–78. http://dx.doi.org/10.1109/23.387358.
Pełny tekst źródłaYum, Bong-Jin, i Seong-Jun Kim. "On parameter design of binary-input-and-binary-output dynamic systems". Quality and Reliability Engineering International 9, nr 6 (listopad 1993): 471–76. http://dx.doi.org/10.1002/qre.4680090603.
Pełny tekst źródłaYang, Sibo, Shusheng Wang, Lanyin Sun, Zhongxuan Luo i Yuan Bao. "Output Layer Structure Optimization for Weighted Regularized Extreme Learning Machine Based on Binary Method". Symmetry 15, nr 1 (16.01.2023): 244. http://dx.doi.org/10.3390/sym15010244.
Pełny tekst źródłaGurevich, Yuri, i Saharon Shelah. "Time polynomial in input or output". Journal of Symbolic Logic 54, nr 3 (wrzesień 1989): 1083–88. http://dx.doi.org/10.2307/2274767.
Pełny tekst źródłaXue, Aijun, i Xiaodan Wang. "Cost-sensitive design of error correcting output codes". Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 232, nr 10 (12.05.2017): 1871–81. http://dx.doi.org/10.1177/0954406217709303.
Pełny tekst źródłaRen, Xiao Guang, Yu Hua Tang i Xin Hai Xu. "Format Optimization for Periodical Snapshot Output in CFD Simulation". Applied Mechanics and Materials 457-458 (październik 2013): 910–18. http://dx.doi.org/10.4028/www.scientific.net/amm.457-458.910.
Pełny tekst źródłaPÉREZ ARCILA, MAURICIO, i MARTIN ALONSO TAMAYO VELEZ. "IMPLEMENTATION OF LEBESGUE SAMPLING METHOD AND DIGITAL SENSORS FOR CONTROLLING THE LEVEL VARIABLE IN A CONTINUOUS SYSTEM". DYNA NEW TECHNOLOGIES 8, nr 1 (11.11.2021): [14 P.]. http://dx.doi.org/10.6036/nt10248.
Pełny tekst źródłaSilva, Carla, Ana Aguiar i Inês Dutra. "Quantum Binary Classification (Student Abstract)". Proceedings of the AAAI Conference on Artificial Intelligence 35, nr 18 (18.05.2021): 15889–90. http://dx.doi.org/10.1609/aaai.v35i18.17941.
Pełny tekst źródłaRahmadhany, Sri. "IDENTIFIKASI POLA KARAKTER ANAK DENGAN ALGORITMA PERCEPTRON". JURNAL TEKNOLOGI INFORMASI 3, nr 1 (13.06.2019): 86. http://dx.doi.org/10.36294/jurti.v3i1.695.
Pełny tekst źródłaRozprawy doktorskie na temat "Binary output"
Grama, Keshava. "Binary matrix for pedestrian tracking in infrared images". Thesis, Edinburgh Napier University, 2013. http://researchrepository.napier.ac.uk/Output/6153.
Pełny tekst źródłaChapin, Patrick Samuel. "Analysis of experiments to validate computer models with binary output". [Ames, Iowa : Iowa State University], 2009. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3389285.
Pełny tekst źródłaOzkan, Ugur. "Application of the constrained implicants set concept to the minimization of binary functions". Thesis, Monterey, California : Naval Postgraduate School, 1990. http://handle.dtic.mil/100.2/ADA239470.
Pełny tekst źródłaThesis Advisor(s): Yang, Chyan ; Butler, Jon T. "September 1990." Description based on title screen as viewed on March 22, 2010. Author(s) subject terms: Constrained Implicants Set Concept, Binary Minimization. Includes bibliographical references (p. 75-76). Also available in print.
Oualla, Hicham. "Contributions à l'identification en boucle ouverte/fermée des systèmes à base de données binaires". Electronic Thesis or Diss., Normandie, 2022. http://www.theses.fr/2022NORMC229.
Pełny tekst źródłaThis thesis is devoted to the identification of systems based on binary data. First, a brief presentation of all the methods of identification of systems based on the use of binary data existing in the literature is given. In the following, we are interested in the problem of open loop identification of systems with binary output and input. We propose methods for the identification of FIR systems and more complex IIR systems with binary input and output. These methods are analyzed and tested by numerical examples. In the rest of this work, we propose first solutions to the problems of closed-loop identification of systems based on binary data. The first solutions are dedicated to binary output systems, the closed loop excitation is assumed to be high resolution. Finally, two methods are proposed for closed loop systems with binary output and input. These solutions are tested on numerical examples to quantify their performances
Ataman, Kaan. "Learning to rank by maximizing the AUC with linear programming for problems with binary output". Diss., University of Iowa, 2007. http://ir.uiowa.edu/etd/151.
Pełny tekst źródłaChaudhari, Pragat. "Analytical Methods for the Performance Evaluation of Binary Linear Block Codes". Thesis, University of Waterloo, 2000. http://hdl.handle.net/10012/904.
Pełny tekst źródłaMedvedieva, S. O., I. V. Bogach, V. A. Kovenko, С. О. Медведєва, І. В. Богач i В. А. Ковенко. "Neural networks in Machine learning". Thesis, ВНТУ, 2019. http://ir.lib.vntu.edu.ua//handle/123456789/24788.
Pełny tekst źródłaThe paper covers the basic principles of Neural Networks’ work. Special attention is paid to Frank Rosenblatt’s model of the network called “perceptron”. In addition, the article touches upon the main programming languages used to write software for Neural Networks.
FALEH, MOHAMAD SALEH. "Conception, realisation et caracterisation de transistors bipolaires de puissance a heterojonction gainp/gaas et comparaison avec les tbh's gaalas/gaas". Toulouse 3, 1998. http://www.theses.fr/1998TOU30027.
Pełny tekst źródłaHui-LiangYu i 游輝亮. "Dual Path Binary Neural Network with Adaptive Output Range". Thesis, 2018. http://ndltd.ncl.edu.tw/handle/nuydfp.
Pełny tekst źródła國立成功大學
資訊工程學系
106
In recent years, deep neural networks (DNNs) have achieved state-of-the-art results in the fields of image recognition, semantic segmentation and machine translation. However, powerful DNNs usually have a large number of parameters and complex calculations. For instance, ImageNet classification challenge winner in 2012, Alex Net, has a model size of about 249MB and 60 million parameters, which needs to perform about 1.5 billion FLOPs to classify a 224 x 224 image. While perform such complex computations, GPUs based machines usually used to speed up training process and inference time. However, for embedded devices, such as smart phones or Internet of Things, there is only a small amount of memory, battery power and computing resources, so it is difficult to deploy DNN to these devices. In the field of model compression, the binary neural network (BNN) is a very promising method, which features are low power consumption and low storage usage, but there is a large gap in prediction accuracy compared with full-precision networks. This thesis proposed a BNN that about the same storage usage as other BNNs and prediction accuracy is close to full-precision network. The method proposed in this thesis has three characteristics: First, the convolution layers have two input sources by dual path method. Second, round the batch normalization output. Third, adjust each layer output by a trainable parameter. The experiments show, our model size is about equal to other BNNs, but the prediction accuracy is much higher. In CIFAR-10 dataset, the prediction accuracy is at least 2.85% higher than other BNNs, even better than ternary network, only 0.69% loss compared to full-precision network. In SVHN dataset, the prediction accuracy is at least 0.21% higher than other BNNs, and even more than 0.58% compared to full-precision network.
"Analysis of experiments to validate computer models with binary output". IOWA STATE UNIVERSITY, 2010. http://pqdtopen.proquest.com/#viewpdf?dispub=3389285.
Pełny tekst źródłaKsiążki na temat "Binary output"
Behrooz, Anahit. Mapping Middle-earth. Bloomsbury Publishing Plc, 2024. http://dx.doi.org/10.5040/9781350290792.
Pełny tekst źródłaNakai, You. Reminded by the Instruments. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780190686765.001.0001.
Pełny tekst źródłaHoste, Eric A. J., John A. Kellum i Norbert Lameire. Definitions, classification, epidemiology, and risk factors of acute kidney injury. Redaktor Norbert Lameire. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780199592548.003.0220_update_001.
Pełny tekst źródłaKhatun, Samia. Australianama. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780190922603.001.0001.
Pełny tekst źródłaCzęści książek na temat "Binary output"
Ye, Tao, i Xuefeng Zhu. "Binary Coded Output Support Vector Machine". W Intelligent Computing Theories and Technology, 47–55. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39482-9_6.
Pełny tekst źródłaBabu, Hafiz Md Hasan. "Multiple-Valued Input Binary-Valued Output Functions". W VLSI Circuits and Embedded Systems, 107–20. Boca Raton: CRC Press, 2022. http://dx.doi.org/10.1201/9781003269182-11.
Pełny tekst źródłaSun, Qilin, Yan Liu, Zhengxue Li, Sibo Yang, Wei Wu i Jiuwu Jin. "The Binary Output Units of Neural Network". W Advances in Neural Networks – ISNN 2013, 250–57. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39065-4_31.
Pełny tekst źródłaLaisney, François, Michael Lechner i Winfried Pohlmeier. "Semi-Nonparametric Estimation of Binary Choice Models Using Panel Data: An Application to the Innovative Activity of German Firms". W Output and Employment Fluctuations, 87–101. Heidelberg: Physica-Verlag HD, 1994. http://dx.doi.org/10.1007/978-3-642-57989-9_7.
Pełny tekst źródłaMorvai, Gusztáv. "Guessing the Output of a Stationary Binary Time Series". W Contributions to Statistics, 207–15. Heidelberg: Physica-Verlag HD, 2003. http://dx.doi.org/10.1007/978-3-642-57410-8_18.
Pełny tekst źródłaLin, Yi, Lucas M. Tabajara i Moshe Y. Vardi. "ZDD Boolean Synthesis". W Tools and Algorithms for the Construction and Analysis of Systems, 64–83. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-99524-9_4.
Pełny tekst źródłaSchirmer, Pascal A., i Iosif Mporas. "Binary versus Multiclass Deep Learning Modelling in Energy Disaggregation". W Springer Proceedings in Energy, 45–51. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-63916-7_6.
Pełny tekst źródłaGalán, Gerhard, i Juris Muñoz. "A new input-output function for binary hopfield neural networks". W Lecture Notes in Computer Science, 311–20. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/bfb0098187.
Pełny tekst źródłaBelfiore, J. C. "A weighted-output symbol-by-symbol decoding algorithm of binary convolutional codes". W Coding Theory and Applications, 154–58. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/3-540-19368-5_17.
Pełny tekst źródłaChaudhari, Narendra S., i Aruna Tiwari. "Extension of Binary Neural Networks for Multi-class Output and Finite Automata". W Neural Information Processing: Research and Development, 211–37. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-39935-3_12.
Pełny tekst źródłaStreszczenia konferencji na temat "Binary output"
Guo, Zhixia, Sitao Li, Jiaxiong Ye, Ruan Yu, Qiyang Xu i Guoping Zhang. "Binary optical resonator with flattop output". W Optical Systems Design and Production, redaktor Fritz Merkle. SPIE, 1999. http://dx.doi.org/10.1117/12.360043.
Pełny tekst źródłaMoskowitz, Ira S., Paul Cotae, Pedro N. Safier i Daniel L. Kang. "Capacity bounds and stochastic resonance for binary input binary output channels". W 2012 Computing, Communications and Applications Conference (ComComAp). IEEE, 2012. http://dx.doi.org/10.1109/comcomap.2012.6154003.
Pełny tekst źródłaShari, Shahrouz, A. Korhan Tanc i Tolga M. Duman. "LDPC code design for binary-input binary-output Z interference channels". W 2015 IEEE International Symposium on Information Theory (ISIT). IEEE, 2015. http://dx.doi.org/10.1109/isit.2015.7282622.
Pełny tekst źródłaQian, Jing, Feifei Gao, Shi Jin, Ling Xing i Junhui Zhao. "Capacity of Ambient Backscatter Communications with Binary Input and Binary Output Channel". W GLOBECOM 2018 - 2018 IEEE Global Communications Conference. IEEE, 2018. http://dx.doi.org/10.1109/glocom.2018.8647136.
Pełny tekst źródłaMoskowitz, Ira S., Paul Cotae i Pedro N. Safier. "Algebraic information theory and stochastic resonance for binary-input binary-output channels". W 2012 46th Annual Conference on Information Sciences and Systems (CISS). IEEE, 2012. http://dx.doi.org/10.1109/ciss.2012.6310786.
Pełny tekst źródłaSwanson, Gary J., James R. Leger i Wilfrid B. Veldkamp. "Tandem Binary Structures for Increased Coupling Efficiency of Laser Beams". W Holography. Washington, D.C.: Optica Publishing Group, 1986. http://dx.doi.org/10.1364/holography.1986.tud5.
Pełny tekst źródłaCao, Jun, i Huimin Ma. "Regression-based parameter optimization for binary output systems". W 2015 3rd International Conference on Information and Communication Technology (ICoICT ). IEEE, 2015. http://dx.doi.org/10.1109/icoict.2015.7231473.
Pełny tekst źródłaYue, Tinghai. "The characterizations of binary vector-output plateaued functions". W 2010 IEEE International Conference on Wireless Communications, Networking and Information Security (WCNIS). IEEE, 2010. http://dx.doi.org/10.1109/wcins.2010.5541807.
Pełny tekst źródłaYue, Tinghai. "A construction of binary vector-output plateaued functions". W 2010 IEEE International Conference on Wireless Communications, Networking and Information Security (WCNIS). IEEE, 2010. http://dx.doi.org/10.1109/wcins.2010.5541808.
Pełny tekst źródłaNguyen, Thuan, i Thinh Nguyen. "Structure of Optimal Quantizer for Binary-Input Continuous-Output Channels with Output Constraints". W 2020 IEEE International Symposium on Information Theory (ISIT). IEEE, 2020. http://dx.doi.org/10.1109/isit44484.2020.9174174.
Pełny tekst źródłaRaporty organizacyjne na temat "Binary output"
Farhi, Edward, i Hartmut Neven. Classification with Quantum Neural Networks on Near Term Processors. Web of Open Science, grudzień 2020. http://dx.doi.org/10.37686/qrl.v1i2.80.
Pełny tekst źródłaSinclair, Samantha, i Sally Shoop. Automated detection of austere entry landing zones : a “GRAIL Tools” validation assessment. Engineer Research and Development Center (U.S.), sierpień 2022. http://dx.doi.org/10.21079/11681/45265.
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