03311nam a22005655i 4500001001800000003000900018005001700027007001500044008004100059020003700100024003500137050001100172072001700183072002300200072001600223245019400239250001800433264006900451300006400520336002600584337002600610338003600636347002400672490005400696505028500750520078601035650002801821650002901849650004901878650004001927650002901967650003601996650002802032650002902060650007102089650004202160650002902202650003602231700008502267700008602352710003402438773002602472776003602498776003602534776003602570830006102606856004602667912001502713999001702728978-3-031-33054-4DE-He21320251030110810.0cr nn 008mamaa230801s2024    sz |    s    |||| 0|eng d  a97830313305449978-3-031-33054-47 a10.1007/978-3-031-33054-42doi 4aTA1634 7aUYQV2bicssc 7aCOM0160002bisacsh 7aUYQV2thema12aA Unifying Framework for Formal Theories of Noveltyh[electronic resource] :bDiscussions, Guidelines, and Examples for Artificial Intelligence /cedited by Terrance Boult, Walter Scheirer.  a1st ed. 2024. 1aCham :bSpringer Nature Switzerland :bImprint: Springer,c2024.  aXV, 110 p. 35 illus., 33 illus. in color.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda1 aSynthesis Lectures on Computer Vision,x2153-10640 aA Unifying Framework for Novelty -- Example Application of Framework: CartPole Domain -- Image Classification -- Novelty in Handwriting Recognition -- Visual Media Caption Domain -- Monopoly Multi-Agent Game Domain -- Related Work -- Prior Perspectives on Novelty and Conclusions.  aThis book presents the first unified formalization for defining novelty across the span of machine learning, symbolic-reasoning, and control and planning-based systems. Dealing with novelty, things not previously seen by a system, is a critical issue for building vision-systems and general intelligent systems. The book presents examples of using this framework to define and evaluate in multiple domains including image recognition image-based open world learning, hand-writing and author analysis, CartPole Control, Image Captioning, and Monopoly. Chapters are written by well-known contributors to this new and emerging field. In addition, examples are provided from multiple areas, such as machine-learning based control problems, symbolic reasoning, and multi-player games. . 0aComputer vision.965546 0aMachine learning.955059 0aImage processingxDigital techniques.964228 0aPattern recognition systems.965547 0aImage processing.965548 0aArtificial intelligence.95844114aComputer Vision.96554924aMachine Learning.95505924aComputer Imaging, Vision, Pattern Recognition and Graphics.96555024aAutomated Pattern Recognition.96555124aImage Processing.96555224aArtificial Intelligence.9584411 aBoult, Terrance.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt9655531 aScheirer, Walter.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt9655542 aSpringerLink (Online service)0 tSpringer Nature eBook08iPrinted edition:z978303133053708iPrinted edition:z978303133055108iPrinted edition:z9783031330568 0aSynthesis Lectures on Computer Vision,x2153-106496555540uhttps://doi.org/10.1007/978-3-031-33054-4  aZDB-2-SXSC  c56226d56226