Eric John Dingwall
John Barry
John Barry
Lauren St John
John Grisham
John Suchet
John Verdon
John Boyne
John F. MacArthur
John Sazaklis
John Steele Gordon
John Steele Gordon
John Gribbin
John Kim
John Connolly
John Manders
John Grisham
John Grisham
Atkins, John
John Baichtal
John Ray
John Markoff
John Christian
John Markoff
John Markoff
John Lutz
John Godwin
John Tierney
John Nikas
John Patrick Walsh
John Nikas
Lisa Lutz
John Stratton Hawley
Sutherland, John
John Tierney
John Durkee
John H. Kranzler
John C. Miles
John C. Miles
John C. Miles
John C. Miles
John C. Warner
John Hughes
John Brantingham
John Connolly
John Connolly
John Bemrose
John Eldredge
John Bemrose
John Connolly
John Lofty
John Grisham
John Connolly
R. Müller-Liebenau
Nancy R. Comley
Sterling Johnson
Thomas Bönisch
Donna Samworth
Thomas Canavan
Lippincott Williams & Wilkins
Sebastià Portell
Grace Paley
Thomas F.H. Schmidt
Mark Grossman
Michael Hosking
Edward Abbey
Mary Wollstonecraft Shelley
Ersébet Csuhaj-Varjú
This two volume set lncs 8634 and lncs 8635 constitutes the refereed conference proceedings of the 39th international symposium on mathematical foundations of computer science, mfcs 2014, held in budapest, hungary, in august 2014.
Karen Schubert
Janusz Dyszlewicz
Enid Blyton
Kangyong Cai
bai hai Chen
Ruth Symes
Fiona Macdonald
Roger Priddy
Paresh Chattopadhyay
Walter Bagehot
Yuanchun Liu
Zhang,Jiguang
Collectif
Yuefan Gan
Horace Walpole
Dominique Boels
Hector Manuel Moya-Cessa
Eric Alagan
Terry Deary
Katy Birchall
Larry Watson
Ava Bradley
Ethel Eljarrat
Gustavo Olague
This book explains the theory and application of evolutionary computer vision, a new paradigm where challenging vision problems can be approached using the techniques of evolutionary computing.
Casimiro Quiji
Tim Walker
Tess Gerritsen
Tara L. Kuther
William W. Johnstone
Paul Christopher
Aly Martinez
Jill Paterson
Li jing
Qi Qi