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Books on the topic 'CNN MODELS'

Author: Grafiati

Published: 11 September 2023

Last updated: 16 April 2024

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1

Gestures Can Create Models that Help Thinking. [New York, N.Y.?]: [publisher not identified], 2019.

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2

Greene, Carol. I can be a model. Chicago: Childrens Press, 1985.

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3

Greene, Carol. I can be a model. Chicago: Childrens Press, 1985.

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4

Trackside scenes you can model. Waukesha, WI: Kalmbach Books, 2003.

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5

Greene, Carol. I can be a model. Chicago: Childrens Press, 1985.

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6

St-Amour, Luc. Realistic Construction Models You Can Make (Vehicles You Can Make Series). East Petersburg, PA: Fox Chapel Publishing Company, 2001.

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7

Dueker, Michael. Can markov switching models predict excess foreign exchange returns? [St. Louis, Mo.]: Federal Reserve Bank of St. Louis, 2001.

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8

Rudd, Jeremy Bay. Can rational expectations sticky-price models explain inflation dynamics? Washington, D.C: Federal Reserve Board, 2003.

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9

1968-, Johnson Kent J., ed. Small railroads you can build. 2nd ed. Waukesha, WI: Kalmbach Pub. Co., 1996.

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10

Antonio Diez de los Rios. Can affine term structure models help us predict exchange rates? [Ottawa]: Bank of Canada, 2006.

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11

Rios-Zertuche, Daniel. Semantic data models can be implemented efficienty: A performance analysis perspective. Toronto: Computer Systems Research Institute, University of Toronto, 1988.

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12

Chari, V. V. Can sticky price models generate volatile and persistent real exchange rates? Cambridge, MA: National Bureau of Economic Research, 2000.

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13

Engel, Charles. Can the Markov switching model forecast exchange rates? Cambridge, MA: National Bureau of Economic Research, 1992.

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14

Sztyber, Władysław Bogdan. Zasada względnej efektywności jako podstawa kształtowania cen. Warszawa: Instytut Finansów, 1986.

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15

Shui wen mo xing can shu gu ji fang fa ji can shu gu ji bu que ding xing yan jiu. Zhengzhou Shi: Huang He shui li chu ban she, 2010.

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16

Kuttner, Kenneth N. Can central banks target bond prices? Cambridge, Mass: National Bureau of Economic Research, 2006.

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17

Riddle, Peter. Easy Lionel layouts you can build. Waukesha, WI: Kalmbach Books, 1998.

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18

Carp, Roger. Classic Lionel display layouts you can build. Waukesha, WI: Kalmbach Books, 2000.

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19

Feldstein, Martin S. Can state taxes redistribute income? Cambridge, MA: National Bureau of Economic Research, 1994.

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20

Casella, Alessandra. Can foreign aid accelerate stabilization? Cambridge, MA: National Bureau of Economic Research, 1994.

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21

Danna, Theresa M. Rollover, Mona Lisa!: How anyone can model for artists. Beverly Hills, CA: Big Guy Pub., 1992.

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22

Bob, Hayden, and Drury George H, eds. HO trackside structures you can build. Waukesha, WI: Kalmbach Pub. Co., 1994.

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23

Neural Networks with R: Smart models using CNN, RNN, deep learning, and artificial intelligence principles. Packt Publishing - ebooks Account, 2017.

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24

Arthouse I Can Make: Models. Ramboro Books PLC, 1997.

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25

Thompson, Erica. Escape from Model Land: How Mathematical Models Can Lead Us Astray and What We Can Do about It. Basic Books, 2022.

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26

Escape from Model Land: How Mathematical Models Can Lead Us Astray and What We Can Do about It. Basic Books, 2022.

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27

Escape from Model Land: How Mathematical Models Can Lead Us Astray and What We Can Do about It. Murray Press, John, 2022.

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28

Thompson, Erica. Escape from Model Land: How Mathematical Models Can Lead Us Astray and What We Can Do about It. Basic Books, 2022.

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29

I Can Make Models (Look & Make). Franklin Watts Ltd, 1998.

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30

I Can Make Models (Look & Make). Franklin Watts Ltd, 1996.

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31

Classic Railroads You Can Model (Model Railroader Books). Kalmbach Publishing Company, 2001.

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32

Lynn, Sara, and Diane James. I Can Make Models (Jump! Starts: Craft). Two-Can Publishing Ltd, 1999.

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33

Boland, Lawrence A. Equilibrium models vs. evolutionary economic models. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780190274320.003.0012.

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This chapter examines the extent to which models based on evolutionary economics can provide a worthy alternative to neoclassical equilibrium models. The chapter discusses the difference between Darwinian and non-Darwinian evolutionary economic models. The chapter includes a discussion of Armen Alchian’s 1950 article that he says is erroneously identified as evolutionary economics. The works of evolutionary economists Ulrich Witt, Jack Vromen, Richard Nelson and Sidney are explained and critically examined. The chapter also considers the question of whether evolutionary economics can ever displace equilibrium economics. Some current evolutionary economic model builders have serious doubts. The chapter concludes with some speculations about going beyond the consideration of the individual firm to include sociological aspects of consumer preference.

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34

Marshall's Tendencies: What Can Economists Know? (Gaston Eyskens Lectures). The MIT Press, 2002.

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35

Marshall's Tendencies: What Can Economists Know? Cambridge, USA: The MIT Press, 2000.

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36

Classic railroads you can model. Waukesha, Wis: Kalmbach Books, 2002.

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37

Miksza, Peter, and Kenneth Elpus. Multilevel Models. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199391905.003.0012.

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This chapter introduces a statistical approach for analyzing nested data structures that both accounts for the dependence of observations due to hierarchical arrangements and allows for testing hypotheses at multiple levels. The most common application of multilevel models is for analyses of objects (e.g., people) nested within groups or clusters of some sort. Multilevel models can also be applied to longitudinal data analyses such that the “levels” do not refer to objects nested within groups but instead refer to multiple measurements (e.g., measures made at different occasions/time points) nested within individuals. The chapter illustrates some of the major considerations and basic steps for performing multilevel analyses so that the reader can begin to imagine how to apply this technique to the reader’s own research questions.

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38

Twenty-One Mental Models That Can Change Policing. Taylor & Francis Group, 2021.

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39

Stursberg, Pete. Your Dream Mentor: How Role Models Can Help. Northwest Publishing, 1994.

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40

Mitchell, Renée J. Twenty-One Mental Models That Can Change Policing. Taylor & Francis Group, 2021.

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41

Back, Kerry E. Factor Models. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780190241148.003.0006.

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The CAPM and factor models in general are explained. Factors can be replaced by the returns or excess returns that are maximally correlated (the projections of the factors). A factor model is equivalent to an affine representation of an SDF and to spanning a return on the mean‐variance frontier. The use of alphas for performance evaluation is explained. Statistical factor models are defined as models in which factors explain the covariance matrix of returns. A proof is given of the Arbitrage Pricing Theory, which states that statistical factors are approximate pricing factors. The CAPM and the Fama‐French‐Carhart model are evaluated relative to portfolios based on sorts on size, book‐to‐market, and momentum.

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42

Harrod, Molly, Sanjay Saint, and Robert W. Stock. Role Models. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190671495.003.0007.

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Attendings understand that their behavior, as physicians, as instructors, as human beings, will most likely be internalized and emulated by some of their learners. As a result, they continually monitor themselves, striving to make sure that they are living up to their personal and professional standards. Attendings often hold themselves to a higher standard than they do their learners. Role modeling is an important part of the teaching process and includes demonstrating how to be a lifelong learner, maintaining professionalism in the face of adversity, and acknowledging the emotional toll that caring for patients can have on oneself. Humor with both learners and patients was common among the attendings, as was expressing the joys of being a doctor.

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43

Rajeev, S. G. Integrable Models. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198805021.003.0009.

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Some exceptional situations in fluid mechanics can be modeled by equations that are analytically solvable. The most famous example is the Korteweg–de Vries (KdV) equation for shallow water waves in a channel. The exact soliton solution of this equation is derived. The Lax pair formalism for solving the general initial value problem is outlined. Two hamiltonian formalisms for the KdV equation (Fadeev–Zakharov and Magri) are explained. Then a short review of the geometry of curves (Frenet–Serret equations) is given. They are used to derive a remarkably simple equation for the propagation of a kink along a vortex filament. This equation of Hasimoto has surprising connections to the nonlinear Schrödinger equation and to the Heisenberg model of ferromagnetism. An exact soliton solution is found.

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44

Bueno, Otávio, and Steven French. Approaching Models. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198815044.003.0002.

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This chapter considers the framework needed in order for mathematical and physical structures to be examined and related, in philosophical terms. We contrast the structuralist account associated with Joseph Sneed, Wolfgang Stegmüller, and others with the models-focused account of Ron Giere. The former, we claim, is heavy on formalism at the expense of a consideration of practice, whereas the latter draws on a number of case studies but omits the crucial formal framework. We suggest rejecting both these extremes in favour of an approach that is appropriately formal, while retaining the ability to represent science as actually practised. We maintain the partial structures account we present here constitutes such an approach. In particular, this framework can accommodate the heuristic role of surplus mathematical structure, as described by Michael Redhead. The exploitation of such structure is a crucial feature of scientific practice that we return to throughout the book.

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45

Bachelet, Dominique, Gitta Lasslop, and John T. Abatzoglou, eds. Climate, Land Use, and Fire: Can Models Inform Management? Frontiers Media SA, 2021. http://dx.doi.org/10.3389/978-2-88966-383-5.

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46

Less-Supervised Segmentation with CNNs: Scenarios, Models and Optimization. Elsevier Science & Technology, 2023.

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47

DiToro, Dominic M. Can TMDL Models Reproduce the Nutrient Loading-Hypoxia Relationship? IWA Publishing, 2015.

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48

Desrosiers, Christian, José Dolz, and Ismail Ben Ayed. Less-Supervised Segmentation with CNNs: Scenarios, Models and Optimization. Elsevier Science & Technology Books, 2023.

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49

Morrison, Margaret. Models and Theories. Edited by Paul Humphreys. Oxford University Press, 2015. http://dx.doi.org/10.1093/oxfordhb/9780199368815.013.32.

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This chapter discusses the relation between models and theories as characterized by the syntactic and semantic views, as well as how that relation is understood in the more scientifically oriented or practice-based accounts of models. It also addresses epistemic issues concerning the model-world relationship and the importance of representation and explanation in assessing how abstract models deliver concrete information. The chapter claims that similarity and isomorphism, construed as general criteria, are often insufficient to characterize the way models relate to their target systems. Although no general theory of modeling can address these issues in a systematic way it is still possible to provide an in-depth philosophical analyses of how the abstraction and idealization present in models can nevertheless tell us important things about the physical world.

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50

Volberda, Henk, Frans A. J. Van Den Bosch, and Kevin Heij. Reinventing Business Models. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198792048.001.0001.

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Although research on business model innovation is flourishing internationally, important questions on the ‘how’, ‘what’, and ‘when’ of this process remain largely unanswered, particularly in regard to the role of top management. Using new knowledge derived from a survey among firms from various industries and several case studies, this book seeks to give us better understanding of ‘how’ firms can innovate their business model, ‘what’ kind of levers management should work on, and ‘when’ management should change the business model. It particularly considers one key question: is it better to replicate existing models or develop new ones? Renewal is especially vital in highly competitive environments. Nonetheless, whatever the environment, high levels of both replication and renewal will be key for a firm to succeed. This book looks at four levers that can be used by managers to innovate their business model: management itself, organizational form, technology, and co-creation with external parties are analysed. Furthermore, specific combinations which strengthen business model innovation are analysed. To help firms, the book also explores the different factors that can either enable or inhibit business model innovation. Through an investigation of replication versus renewal and of strategy-driven versus client-driven change, four distinct modes of business model innovation are identified: exploit and improve (replication which is strategy-driven); exploit and connect (replication which is customer-driven); explore and connect (renewal which is customer-driven); and explore and dominate (renewal which is strategy-driven). This book ends with a list of managerial dos and don’ts for business model innovation.

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