LEADER 01067nam--2200385---450- 001 990000724590203316 005 20050216133528.0 010 $a88-7697-052-5 035 $a0072459 035 $aUSA010072459 035 $a(ALEPH)000072459USA01 035 $a0072459 100 $a20011108d1996----km-y0itay0103----ba 101 $aita 102 $aIT 105 $a||||||||001yy 200 1 $aT come Tango$eun invito a muoversi al di là degli stereotipi$fMeri lao 210 $aRoma$cMelusina$d1996 215 $a335 p.$cill.$d21 cm 410 $12001 461 1$1001-------$12001 606 0 $aTango 676 $a793.33 700 1$aLAO,$bMeri$0448622 801 0$aIT$bsalbc$gISBD 912 $a990000724590203316 951 $aXIII.4. 2(VARIE COLL 1251/7)$b136098 LM$cVARIE COLL 959 $aBK 969 $aUMA 979 $aPATTY$b90$c20011108$lUSA01$h1405 979 $c20020403$lUSA01$h1721 979 $aPATRY$b90$c20040406$lUSA01$h1650 979 $aCOPAT2$b90$c20050216$lUSA01$h1335 996 $aT come Tango$9962559 997 $aUNISA LEADER 01949nam 2200613 a 450 001 9910455682103321 005 20210114031913.0 010 $a1-4175-0533-8 035 $a(CKB)111090860502202 035 $a(OCoLC)568004610 035 $a(CaPaEBR)ebrary10103880 035 $a(SSID)ssj0000194315 035 $a(PQKBManifestationID)11157003 035 $a(PQKBTitleCode)TC0000194315 035 $a(PQKBWorkID)10232582 035 $a(PQKB)10232541 035 $a(MiAaPQ)EBC3417089 035 $a(EXLCZ)99111090860502202 100 $a20150424d2002 uy| 0 101 0 $aeng 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacontent 200 10$aLosing Work, Moving On$b[electronic resource] $eInternational Perspectives on Worker Displacement /$fPeter Joseph Kuhn 210 $aKalamazoo, MI, USA $cW. E. Upjohn Institute for Employment Research$d2002 210 $cW. E. Upjohn Institute for Employment Research 215 $a1 online resource (559 p.) 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a0-88099-234-4 320 $aIncludes bibliographical references and index. 606 $aBUSINESS & ECONOMICS$2bisac 606 $aDisplaced workers$vCase studies 606 $aUnemployment$vCase studies 606 $aUnemployed$vCase studies 606 $aLabor$2bisac 606 $aMarketing & Sales$2HILCC 606 $aCommerce$2HILCC 606 $aBusiness & Economics$2HILCC 615 7$aBUSINESS & ECONOMICS 615 0$aDisplaced workers 615 0$aUnemployment 615 0$aUnemployed 615 7$aLabor 615 7$aMarketing & Sales 615 7$aCommerce 615 7$aBusiness & Economics 676 $a331.13/7 700 $aKuhn$b Peter Joseph$0891670 801 0$bPQKB 801 2$bAzTeS 906 $aBOOK 912 $a9910455682103321 996 $aLosing Work, Moving On$91991492 997 $aUNINA LEADER 08072nam 22007575 450 001 996495566503316 005 20230202010542.0 010 $a3-031-18916-7 024 7 $a10.1007/978-3-031-18916-6 035 $a(MiAaPQ)EBC7126605 035 $a(Au-PeEL)EBL7126605 035 $a(CKB)25208126500041 035 $a(DE-He213)978-3-031-18916-6 035 $a(PPN)265855675 035 $a(EXLCZ)9925208126500041 100 $a20221012d2022 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aPattern Recognition and Computer Vision$b[electronic resource] $e5th Chinese Conference, PRCV 2022, Shenzhen, China, November 4?7, 2022, 2022, Proceedings, Part IV /$fedited by Shiqi Yu, Zhaoxiang Zhang, Pong C. Yuen, Junwei Han, Tieniu Tan, Yike Guo, Jianhuang Lai, Jianguo Zhang 205 $a1st ed. 2022. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2022. 215 $a1 online resource (752 pages) 225 1 $aLecture Notes in Computer Science,$x1611-3349 ;$v13537 300 $aIncludes index. 311 08$aPrint version: Yu, Shiqi Pattern Recognition and Computer Vision Cham : Springer,c2022 9783031189159 327 $aImage Processing and Low-level Vision -- Video Deraining via Temporal Discrepancy Learning -- Multi-priors Guided Dehazing Network Based on Knowledge Distillation -- DLMP-Net: a dynamic yet lightweight multi-pyramid network for crowd density estimation -- CHENet: Image to Image Chinese Handwriting Eraser -- Identidication method for rice pests with small sample size problem combining deep learning and metric learning -- Boundary-Aware Polyp Segmentation Network -- SUDANet:A Siamese UNet with Dense Attention Mechanism for Remote Sensing Image Change Detection -- A Local-Global Self-attention Interaction Network for RGB-D Cross-modal Person Re-identification -- A RAW Burst Super-Resolution Method with Enhanced Denoising -- Unpaired and Self-supervised Optical Coherence Tomography Angiography Super-resolution -- Multi-Feature Fusion Network for Single Image Dehazing -- LAGAN: Landmark Aided Text to Face Sketch Generation -- DMF-CL: Dense Multi-scale Feature Contrastive Learning for Semantic segmentation of Remote-sensing images -- Image derain method for generative adversarial network based on wavelet high frequency feature fusion -- GPU-Accelerated Infrared Patch-Image Model for Small Target Detection -- Hyperspectral and Multispectral Image Fusion Based on Unsupervised Feature Mixing and Reconstruction Network -- Information Adversarial Disentanglement for Face Swapping -- A Dense Prediction ViT Network for Single Image Bokeh Rendering -- Multi-scale Coarse-to-fine Network for Demoiring -- Learning Contextual Embedding Deep Networks for Accurate and Efficient Image Deraining -- A Stage-Mutual-Ane Network for Single Remote Sensing Image Super-Resolution -- Style-based Attentive Network for Real-World Face Hallucination -- Cascade Scale-aware Distillation Network for Lightweight Remote Sensing Image Super-Resolution -- Few-Shot Segmentation via Rich Prototype Generation and Recurrent Prediction Enhancement -- Object Detection, Segmentation and Tracking -- TAFDet: A Task Awareness Focal Detector for Ship Detection in SAR Images -- MSDNet:Multi-scale Dense Networks for Salient Object Detection -- WaveSNet: Wavelet Integrated Deep Networks for Image Segmentation -- Infrared Object Detection Algorithm Based on Spatial Feature Enhancement -- Object Detection Based on Embedding Internal and External Knowledge -- ComLoss: A Novel Loss towards More Compact Predictions for Pedestrian Detection -- Remote sensing image detection based on attention mechanism and YOLOv5 -- Detection of Pin Defects in Transmission Lines Based on Dynamic Receptive Field -- Identification of bird s nest hazard level of transmission line based on improved yolov5 and location constraints -- Image Magnification Network for Vessel Segmentation in OCTA Images -- CFA-Net: Cross-level Feature Fusion and Aggregation Network for Salient Object Detection -- Disentangled Feature Learning for Semi-supervised Person Re-identification -- Detection Beyond What and Where: A Benchmark for Detecting Occlusion State -- Weakly Supervised Object Localization with Noisy-Label Learning -- Enhanced Spatial Awareness For Deep Interactive Image Segmentation -- Anchor-Free Location Refinement Network for Small License Plate Detection -- Multi-View LiDAR Guided Monocular 3D Object Detection -- Dual Attention-guided Network for Anchor-free Apple Instance Segmentation in Complex Environments -- Attention-Aware Feature Distillation for Object Detection in Decompressed Images -- Cross-Stage Class-Specific Attention for Image Semantic Segmentation -- Defect Detection for High Voltage Transmission Lines Based on Deep Learning -- ORION: Orientation-Sensitive Object Detection -- An Infrared Moving Small Object Detection Method Based on Trajectory Growth -- Two-stage Object Tracking Based on Similarity Measurement for Fused Features of Positive and Negative Samples -- PolyTracker: Progressive Contour Regression for Multiple Object Tracking and Segmentation -- Dual-branch Memory Network for Visual Object Tracking -- Instance-wise Contrastive Learning for Multi-Object Tracking -- Information Lossless Multi-Modal Image Generation for RGB-T Tracking -- JFT: A Robust Visual Tracker Based on Jitter Factor and Global Registration -- Caged Monkey Dataset: A New Benchmark for Caged Monkey Pose Estimation -- WTB-LLL: A Watercraft Tracking Benchmark Derived by Low-light-level Camera -- Dualray: Dual-view X-ray Security Inspection Benchmark and Fusion Detection Framework. 330 $aThe 4-volume set LNCS 13534, 13535, 13536 and 13537 constitutes the refereed proceedings of the 5th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2022, held in Shenzhen, China, in November 2022. The 233 full papers presented were carefully reviewed and selected from 564 submissions. The papers have been organized in the following topical sections: Theories and Feature Extraction; Machine learning, Multimedia and Multimodal; Optimization and Neural Network and Deep Learning; Biomedical Image Processing and Analysis; Pattern Classification and Clustering; 3D Computer Vision and Reconstruction, Robots and Autonomous Driving; Recognition, Remote Sensing; Vision Analysis and Understanding; Image Processing and Low-level Vision; Object Detection, Segmentation and Tracking. 410 0$aLecture Notes in Computer Science,$x1611-3349 ;$v13537 606 $aImage processing?Digital techniques 606 $aComputer vision 606 $aArtificial intelligence 606 $aComputer engineering 606 $aComputer networks 606 $aApplication software 606 $aComputer systems 606 $aComputer Imaging, Vision, Pattern Recognition and Graphics 606 $aArtificial Intelligence 606 $aComputer Engineering and Networks 606 $aComputer Communication Networks 606 $aComputer and Information Systems Applications 606 $aComputer System Implementation 615 0$aImage processing?Digital techniques. 615 0$aComputer vision. 615 0$aArtificial intelligence. 615 0$aComputer engineering. 615 0$aComputer networks. 615 0$aApplication software. 615 0$aComputer systems. 615 14$aComputer Imaging, Vision, Pattern Recognition and Graphics. 615 24$aArtificial Intelligence. 615 24$aComputer Engineering and Networks. 615 24$aComputer Communication Networks. 615 24$aComputer and Information Systems Applications. 615 24$aComputer System Implementation. 676 $a006.37 702 $aYu$b Shiqi 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996495566503316 996 $aPattern recognition and computer vision$91972598 997 $aUNISA LEADER 01048nam a2200277 i 4500 001 991000632199707536 005 20020503192906.0 008 940609s1987 us ||| | eng 020 $a0838426956 035 $ab10106248-39ule_inst 035 $aLE02519494$9ExL 040 $aFac. 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