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1

Pomplun, Marc, and Junichi Suzuki. Developing and applying biologically-inspired vision systems: Interdisciplinary concepts. Information, Science, Reference, 2013.

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2

Li, Hua Harry. Video Data Compression for Multimedia Computing: Statistically Based and Biologically Inspired Techniques. Springer US, 1997.

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3

Cristóbal, Gabriel, Laurent Perrinet, and Matthias S. Keil, eds. Biologically Inspired Computer Vision. Wiley-VCH Verlag GmbH & Co. KGaA, 2015. http://dx.doi.org/10.1002/9783527680863.

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4

Overington, Ian. Computer vision: A unified, biologically-inspired approach. Elsevier, 1992.

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5

Dressler, Falko, and Iacopo Carreras, eds. Advances in Biologically Inspired Information Systems. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-72693-7.

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6

Hinchey, Mike, Bernd Kleinjohann, Lisa Kleinjohann, et al., eds. Distributed, Parallel and Biologically Inspired Systems. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15234-4.

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7

1970-, Timmis Jonathan, ed. Artificial immune systems: A new computational intelligence approach. Springer, 2002.

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8

Sanaz, Mostaghim, Randall Marcus, Lewis Andrew, and SpringerLink (Online service), eds. Biologically-Inspired Optimisation Methods: Parallel Algorithms, Systems and Applications. Springer Berlin Heidelberg, 2009.

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9

Bio-inspired computing and networking. CRC Press, 2011.

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10

Kambayashi, Yasushi. Multi-agent applications with evolutionary computation and biologically inspired technologies: Intelligent techniques for ubiquity and optimization. Medical Information Science Reference, 2010.

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11

Chen, Shu-Heng. Multi-agent applications with evolutionary computation and biologically inspired technologies: Intelligent techniques for ubiquity and optimization. Medical Information Science Reference, 2010.

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12

Claudio, Mattiussi, ed. Bio-inspired artificial intelligence: Theories, methods, and technologies. MIT Press, 2009.

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13

China) International Conference on Communications and Networking in China (8th 2013 Guilin. 2013 8th First International Conference on Communications and Networking in China: (CHINACOM 2013) : Guilin, China, 14-16 2013. IEEE, 2013.

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14

Păun, Andrei. Computability of the DNA and cells: Splicing and membrane computing. SBEB Pub., 2008.

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15

International Conference on Communications and Networking in China (1st 2006 Beijing, China). 2006 First International Conference on Communications and Networking in China: Beijing, China, 25-27 October 2006. IEEE Service Center, 2006.

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16

Workshop on Bio-Inspired Design of Networks (1st 2007 Cambridge, England). Bio-inspired computing and communication: First Workshop on Bio-Inspired Design of Networks, BIOWIRE 2007 Cambridge, UK, April 2-5, 2007 revised selected papers. Springer, 2008.

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17

Pietro, Liò, ed. Bio-inspired computing and communication: First Workshop on Bio-Inspired Design of Networks, BIOWIRE 2007 Cambridge, UK, April 2-5, 2007 revised selected papers. Springer, 2008.

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18

Workshop on Bio-Inspired Design of Networks (1st 2007 Cambridge, England). Bio-inspired computing and communication: First Workshop on Bio-Inspired Design of Networks, BIOWIRE 2007 Cambridge, UK, April 2-5, 2007 revised selected papers. Springer, 2008.

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19

Melin, Patricia. Bio-inspired Hybrid Intelligent Systems for Image Analysis and Pattern Recognition. Springer-Verlag Berlin Heidelberg, 2009.

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20

Dressler, Falko. Self-organization in sensor and actor networks. John Wiley & Sons, 2007.

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21

Machado, Penousal. Evolutionary and Biologically Inspired Music, Sound, Art and Design: Second International Conference, EvoMUSART 2013, Vienna, Austria, April 3-5, 2013. Proceedings. Springer Berlin Heidelberg, 2013.

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22

Lishan, Kang, Liu Yong 1966-, and Zeng Sanyou, eds. Evolvable systems: From biology to hardware : 7th international conference, ICES 2007, Wuhan, China, September 21-23, 2007 : proceedings. Springer, 2007.

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23

Joan, Cabestany, ed. Bio-inspired systems: Computational and ambient intelligence : 10th International Work-Conference on Artificial Neural Networks, IWANN 2009, Salamanca, Spain, June 10-12, 2009 : proceedings. Springer-Verlag, 2009.

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24

TC10, Working Conference on Distributed and Parallel Embedded Systems (7th 2010 Brisbane Qld ). Distributed, parallel and biologically inspired systems: 7th IFIP TC 10 Working Conference, DIPES 2010 and 3rd IFIP TC 10 International Conference, BICC 2010, held as part of WCC 2010, Brisbane, Australia, September 20-23, 2010, proceedings. Springer, 2010.

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25

Yong, Gan, Premaratne Prashan, Han Kyungsook, and SpringerLink (Online service), eds. Bio-Inspired Computing and Applications: 7th International Conference on Intelligent Computing, ICIC 2011, Zhengzhou,China, August 11-14. 2011, Revised Selected Papers. Springer Berlin Heidelberg, 2012.

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26

Carlos, Martín Vide, Truthe Bianca, and SpringerLink (Online service), eds. Theory and Practice of Natural Computing: First International Conference, TPNC 2012, Tarragona, Spain, October 2-4, 2012. Proceedings. Springer Berlin Heidelberg, 2012.

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27

Li-cheng, Jiao, ed. Advances in natural computation: Second international conference, ICNC 2006, Xi'an, China, September 24-28, 2006 : proceedings. Springer, 2006.

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28

Dudek, Piotr. Vision. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199674923.003.0014.

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Vision is a sensory modality of primary importance to many animal species. The efficient implementation of visual perception is also one of the main challenges in the design of intelligent robotic systems. This chapter reviews the principles of operation and key features of the early stages of biological vision systems. Following the observation that visual information processing starts in the eye, it reviews several approaches to constructing biomimetic artificial vision systems. It presents devices inspired by the morphology of the insects’ compound eyes, and devices tightly integrating imag
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29

(Editor), Auke Jan Ijspeert, Toshimitsu Masuzawa (Editor), and Shinji Kusumoto (Editor), eds. Biologically Inspired Approaches to Advanced Information Technology: Second International Workshop, BioADIT 2006, Osaka, Japan 26-27, 2006, Proceedings (Lecture Notes in Computer Science). Springer, 2006.

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30

Herault, Jeanny, Gabriel Cristobal, Matthias S. Keil, and Laurent Perrinet. Biologically Inspired Computer Vision: Fundamentals and Applications. Wiley-VCH Verlag GmbH, 2015.

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31

Vasilaki, Eleni. A biologically inspired dynamic model for vision. 2003.

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32

Kim, Minjun, Agung Julius, and U. Kei Cheang. Microbiorobotics: Biologically Inspired Microscale Robotic Systems. Elsevier Science & Technology Books, 2017.

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33

Kim, Minjun, and Julius Agung. Microbiorobotics: Biologically Inspired Microscale Robotic Systems. Elsevier Science & Technology Books, 2016.

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34

Microbiorobotics Biologically Inspired Microscale Robotic Systems. William Andrew Publishing, 2012.

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35

Castro, Leandro Nunes de, and Jonathan Timmis. Artificial Immune Systems: A New Computational Intelligence Approach. Springer, 2002.

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36

Lewis, Andrew, Sanaz Mostaghim, and Marcus Randall. Biologically-Inspired Optimisation Methods: Parallel Algorithms, Systems and Applications. Springer, 2010.

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37

Dressler, Falko, and Iacopo Carreras. Advances in Biologically Inspired Information Systems: Models, Methods, and Tools. Springer, 2010.

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38

Bioinspired Models Of Network Information And Computing Systems 4th International Conference Revised Selected Papers. Springer, 2010.

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39

Dehuri, Satchidananda, Sung-Bae Cho, Bhabani Shankar Prasad Mishra, Margarita N. Favorskaya, and Pradeep Kumar Mallick. Biologically Inspired Techniques in Many-Criteria Decision Making: International Conference on Biologically Inspired Techniques in Many-Criteria ... and Analytics in Intelligent Systems ). Springer, 2020.

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40

Harry, Li Hua, Sun Shan 1960-, and Derin Haluk, eds. Video data compression for multimedia computing: Statistically based and biologically inspired techniques. Kluwer Academic Publishers, 1997.

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41

Video Data Compression for Multimedia Computing: Statistically Based and Biologically Inspired Techniques. Springer, 2012.

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42

1966-, Arena Paolo, and International Centre for Mechanical Sciences., eds. Dynamical systems, wave-based computation and neuro-inspired robots. Springer, 2008.

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43

Vassiliadis, Vassilios, and Georgios Dounias. Algorithmic Trading based on Biologically Inspired Algorithms. Edited by Shu-Heng Chen, Mak Kaboudan, and Ye-Rong Du. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780199844371.013.11.

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The chapter discusses algorithmic trading, which refers to any automated process, consisting of a number of interconnected components, whose main aim is to perform financial transactions of any kind. Its chief advantage lies in the fact that human intervention is minimized to an acceptable extent. This is quite desirable because nowadays numerous factors affect financial decisions. Financial managers are able to deal with a limited amount of information. There are many ways to implement algorithmic trading systems. This chapter aims to highlight the efficiency of biologically inspired methodol
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44

Engelbrecht, Andries P., Ajith Abraham, Václav Snášel, Azah Kamilah Muda, Nelishia Pillay, and Mathys C. du Plessis. Advances in Nature and Biologically Inspired Computing: Proceedings of the 7th World Congress on Nature and Biologically Inspired Computing ... in Intelligent Systems and Computing ). Springer, 2015.

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45

Eldridge, Alice, and Oliver Bown. Biologically Inspired and Agent-Based Algorithms for Music. Edited by Roger T. Dean and Alex McLean. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780190226992.013.18.

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This chapter examines a range of approaches to algorithmic music making inspired by biological systems, and considers topics at the intersection of contemporary music, computer science, and computational creativity. A summary of core precursor movements both within and beyond musical practice (A Life, cybernetics, systems art, etc.) sets the scene, before core models and algorithms are introduced and illustrated. These include evolutionary algorithms, agent-based modelling and self-organizing systems, adaptive behaviour and interactive performance systems, and ecosystemic approaches to composi
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46

(Editor), Falko Dressler, and Iacopo Carreras (Editor), eds. Advances in Biologically Inspired Information Systems: Models, Methods, and Tools (Studies in Computational Intelligence). Springer, 2007.

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47

Freedman, Linda. ‘Energy is Eternal Delight’. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198813279.003.0007.

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Gary Snyder’s ecopoetical reading of Blake married Blake’s energetic principle with anarchist politics and a deep appreciation of Zen Buddhism and contrasted it with the deadening impact of fossil fuel technology on the earth. Michael McClure equated Blakean delight with animality and biological unpredictability which he used to oppose the uncompromising rigidity of political ideology and systemic control. Latent in the history of the earth, animal sensuality, and continually shifting systems of biological reorganization, McClure and Snyder perceived Blakean delight as the energetic lifeblood
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48

B, Bajić V., and Tan Tin Wee, eds. Information processing and living systems. Imperial College Press, 2005.

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49

Floreano, Dario, Ronald C. Arkin, and Claudio Mattiussi. Bio-Inspired Artificial Intelligence: Theories, Methods, and Technologies. MIT Press, 2008.

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50

Floreano, Dario, and Claudio Mattiussi. Bio-Inspired Artificial Intelligence: Theories, Methods, and Technologies. MIT Press, 2008.

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