LEADER 02431nam 2200649 a 450 001 9910791668503321 005 20160607153838.0 010 $a1-4462-4407-5 010 $a9786612956577 010 $a0-85702-447-7 010 $a1-282-95657-4 010 $a1-4462-0252-6 035 $a(CKB)2560000000054881 035 $a(EBL)635484 035 $a(OCoLC)698105715 035 $a(SSID)ssj0000471312 035 $a(PQKBManifestationID)12123762 035 $a(PQKBTitleCode)TC0000471312 035 $a(PQKBWorkID)10427997 035 $a(PQKB)10221446 035 $a(MiAaPQ)EBC635484 035 $a(StDuBDS)EDZ0000018654 035 $a(FINmELB)ELB131312 035 $a(PPN)227912950 035 $a(EXLCZ)992560000000054881 100 $a20110121d2009 fy| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt 182 $cc 183 $acr 200 10$aMethodology for creating business knowledge$b[electronic resource] /$fIngeman Arbnor & Bjo??rn Bjerke 205 $a3rd ed. 210 $aLos Angeles, [Calif.] ;$aLondon $cSAGE$dc2009 215 $a1 online resource (xxv, 433 p.) $cill 300 $aTranslation of: Fo?retagsekonomisk metodla?ra. 300 $aPrevious ed.: 1997. 311 $a1-84787-059-7 311 $a1-84787-058-9 320 $aIncludes bibliographical references (p. [428]-430) and index. 327 $apt. 1. Introduction to research methodology -- pt. 2. Three methodological views -- pt. 3. Methodology -- pt. 4. Approaching methodology -- pt. 5. Methodology of complementarity. 330 8 $aThis book presents and compares three different methodologies for gaining business knowledge: analytic, systems and actors. The consequences of using each approach in various practical and theoretical situations are examined. 606 $aManagerial economics$xMethodology 606 $aBusiness$xResearch$xMethodology 606 $aOrganizational learning$xCost effectiveness 615 0$aManagerial economics$xMethodology. 615 0$aBusiness$xResearch$xMethodology. 615 0$aOrganizational learning$xCost effectiveness. 676 $a302.35 700 $aArbnor$b Ingeman$f1949-$028023 701 $aBjerke$b Bjo?rn$f1941-$028024 801 0$bStDuBDS 801 1$bStDuBDS 906 $aBOOK 912 $a9910791668503321 996 $aMethodology for creating business knowledge$93744508 997 $aUNINA LEADER 02538nam 2200709z- 450 001 9910557791503321 005 20220111 035 $a(CKB)5400000000045473 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/77165 035 $a(oapen)doab77165 035 $a(EXLCZ)995400000000045473 100 $a20202201d2021 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aMachine Learning/Deep Learning in Medical Image Processing 210 $aBasel, Switzerland$cMDPI - Multidisciplinary Digital Publishing Institute$d2021 215 $a1 online resource (132 p.) 311 08$a3-0365-2664-1 311 08$a3-0365-2665-X 330 $aMany recent studies on medical image processing have involved the use of machine learning (ML) and deep learning (DL). This special issue, "Machine Learning/Deep Learning in Medical Image Processing", has been launched to provide an opportunity for researchers in the area of medical image processing to highlight recent developments made in their fields with ML/DL. Seven excellent papers that cover a wide variety of medical/clinical aspects are selected in this special issue. 606 $aTechnology: general issues$2bicssc 610 $aairway volume analysis 610 $aanimal rat models 610 $aartificial intelligence 610 $aCADx 610 $aclassification models 610 $acolon cancer 610 $acolon polyps 610 $acomputed tomography 610 $aconvolutional neural network 610 $aconvolutional neural networks 610 $acoronary artery disease 610 $adata augmentation 610 $adeep learning 610 $ahandcrafted 610 $amachine learning 610 $amedical image segmentation 610 $amicroscopic 610 $an/a 610 $aneoplasm metastasis 610 $aOCT 610 $aoptical biopsy 610 $aoral carcinoma 610 $aovarian neoplasms 610 $apancreas 610 $aprostate carcinoma 610 $aradiation exposure 610 $asegmentation 610 $aSPECT MPI scans 610 $atomography 610 $atransfer learning 610 $ax-ray computed 615 7$aTechnology: general issues 700 $aNishio$b Mizuho$4edt$01297577 702 $aNishio$b Mizuho$4oth 906 $aBOOK 912 $a9910557791503321 996 $aMachine Learning$93024568 997 $aUNINA