{"text_format":"2","workbook":"xls","n_sheets":1,"sheets":["report2"],"not_rendered":{"charts":0,"images":0,"macros":0,"external_links":1,"defined_names":2,"comments":0,"pivot_tables":0},"unopened":[],"bounds":{"document_bytes":16777216,"sheet_cells":100000,"run_cost":"one","rows_first":2000,"rows_last":500,"rows_between":2000,"halvings":0,"cell_chars":16384,"cell_head_chars":4096},"cells_cut":0,"cells_raw":0,"read":"whole","date_system":"1900","formulas":"cached_only"}

{"sheet":"report2","index":0,"n_rows":34,"n_cols":5,"rows_kept":34,"cut":false,"hidden":false,"merged":[[0,2,0,3],[0,4,0,5],[1,2,1,3],[1,4,1,5],[2,2,2,3],[2,4,2,5],[3,2,3,3],[4,2,4,3],[5,2,5,3],[6,2,6,3],[7,2,7,3],[8,2,8,3],[9,2,9,3],[11,2,11,3],[11,4,11,5],[12,2,12,3],[12,4,12,5],[13,2,13,3],[13,4,13,5],[14,2,14,3],[15,2,15,3],[16,2,16,3],[17,2,17,3],[18,2,18,3],[19,2,19,3],[20,2,20,3],[27,2,27,3],[28,2,28,3],[32,2,32,3]],"flags":["formulas_cached_only"]}
[null,"1.","Record Nr.",null,"UNINA990004088330403321"]
[null,null,"Autore",null,"Lawson, John Howard"]
[null,null,"Titolo",null,"Teoria e tecnica della sceneggiatura / John Howard Lawson ; edizione italiana a cura di Fernaldo Di Giammatteo"]
[null,null,"Pubbl/distr/stampa",null,"Roma : Bianco e Nero, stampa 1951"]
[null,null,"Descrizione fisica",null,"357 p. ; 20 cm"]
[null,null,"Disciplina",null,"791.437"]
[null,null,"Locazione",null,"FLFBC"]
[null,null,"Collocazione",null,"791.437 LAW 1"]
[null,null,"Lingua di pubblicazione",null,"Italiano"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,"2.","Record Nr.",null,"UNINA9910298568103321"]
[null,null,"Autore",null,"Nath Vishnu"]
[null,null,"Titolo",null,"Autonomous Robotics and Deep Learning / / by Vishnu Nath, Stephen E. Levinson"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014"]
[null,null,"ISBN",null,"3-319-05603-4"]
[null,null,"Edizione",null,"[1st ed. 2014.]"]
[null,null,"Descrizione fisica",null,"1 online resource (73 p.)"]
[null,null,"Collana",null,"SpringerBriefs in Computer Science, , 2191-5768"]
[null,null,"Disciplina",null,"629.892"]
[null,null,"Soggetti",null,"Artificial intelligence"]
[{"$nulls":4},"Optical data processing"]
[{"$nulls":4},"User interfaces (Computer systems)"]
[{"$nulls":4},"Artificial Intelligence"]
[{"$nulls":4},"Image Processing and Computer Vision"]
[{"$nulls":4},"User Interfaces and Human Computer Interaction"]
[{"$nulls":4},"Computer Imaging, Vision, Pattern Recognition and Graphics"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references."]
[null,null,"Nota di contenuto",null,"Introduction -- Overview of Probability and Statistics -- Primer on Matrices and Determinants -- Robot Kinematics -- Computer Vision -- Machine Learning -- Experimental Results -- Future Direction."]
[null,null,null,"Sommario/riassunto","This Springer Brief examines the combination of computer vision techniques and machine learning algorithms necessary for humanoid robots to develop “true consciousness.” It illustrates the critical first step towards reaching “deep learning,” long considered the holy grail for machine learning scientists worldwide. Using the example of the iCub, a humanoid robot which learns to solve 3D mazes, the book explores the challenges to create a robot that can perceive its own surroundings. Rather than relying solely on human programming, the robot uses physical touch to develop a neural map of its environment and learns to change the environment for its own benefit. These techniques allow the iCub to accurately solve any maze, if a solution exists, within a few iterations. With clear analysis of the iCub experiments and its results, this Springer Brief is ideal for advanced level students, researchers and professionals focused on computer vision, AI and machine learning."]