LEADER 05100nam 2200649 450 001 9910828013103321 005 20200520144314.0 010 $a3-11-047813-7 010 $a3-11-047872-2 024 7 $a10.1515/9783110478723 035 $a(CKB)3850000000001136 035 $a(DE-B1597)466511 035 $a(OCoLC)979690724 035 $a(DE-B1597)9783110478723 035 $a(Au-PeEL)EBL4835264 035 $a(CaPaEBR)ebr11387417 035 $a(OCoLC)971951080 035 $a(MiAaPQ)EBC4835264 035 $a(PPN)202114708 035 $a(EXLCZ)993850000000001136 100 $a20170608h20172017 uy 0 101 0 $ager 135 $aurcnu|||||||| 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 10$aNeue Quellen zum Prozessrecht der Ptolemaerzeit $eGerichtsakten aus der Trierer Papyrussammlung (P. Trier I) /$fvon Barbel Kramer und Carlos Ma. Sanchez-Moreno Ellart 210 1$aBerlin, Germany ;$aBoston, [Massachusetts] :$cDe Gruyter,$d2017. 210 4$d©2017 215 $a1 online resource (293 pages) $ccolor illustrations 225 1 $aArchiv fur Papyrusforschung und verwandte Gebiete ;$vBeiheft 36 311 $a3-11-047424-7 320 $aIncludes bibliographical references and index. 327 $tFrontmatter -- $tInhaltsverzeichnis -- $tVorwort -- $tZeichenerklärung -- $t1. Die neuen Quellen -- $t2. Zum ptolemäischen Gerichtswesen -- $t3. Die Prozeßvorbereitung -- $t4. Der Beweis -- $t5. Das Zeugnis -- $t1. Vorladung wegen Nichtrückzahlung eines Gelddarlehens (Amyntas gegen Archepolis) -- $t2. Vorladung wegen Nichtrückzahlung eines Gelddarlehens (Amyntas gegen Archepolis) -- $t3. Vorladung wegen Nichtrückzahlung eines Gelddarlehens (Aniketos gegen Ptolemaios) -- $t4. Vorladung wegen Nichtrückzahlung eines Arakos-Darlehens (Antigonos gegen NN) -- $t5. Vorladung wegen Nichtrückzahlung eines Weizendarlehens (Apollodoros gegen Botrichos) -- $t6. Vorladung wegen Nichtrückzahlung eines Weizendarlehens (NN gegen Ptolemaios) -- $t7. Ende einer Vorladung mit Signalement zweier Ladungszeugen -- $t8. Signalement zweier Ladungszeugen -- $t9. Zeugenaussage des Syngraphophylax Protarchos mit Abschrift eines Vertrags über ein Naturaldarlehen -- $t10. Zeugenaussage des Syngraphophylax Demetrios zugunsten des Hermaios im Prozess gegen Dionysodoros mit angefügtem Gelddarlehensvertrag -- $t11. Zeugenaussage eines Syngraphophylax zugunsten des Apollonios im Prozess gegen Zenon -- $t12. Prodomatischer Pachtvertrag zwischen Bakchios und Pyrrhos -- $t13. Fragment mit Erwähnung eines Pachtvertrags -- $t14. Bericht über einen Rechtsstreit? -- $tBibliographie -- $tKorrekturvorschläge -- $tIndizes zu P.Trier I 330 $aDie neuen Gerichtsakten aus dem Dikasterion von Herakleopolis in Unterägypten umfassen Vorladungen, Zeugenaussagen und Verträge in griechischer Sprache vom Anfang des 2. Jhs. vor Chr. Bearbeitungsvermerke von Gerichtsdienern deuten darauf hin, dass sie im Büro des Eisagogeus (etwa: Geschäftsführer) zur Verwendung im Prozess vorbereitet wurden. Danach wurden sie dort archiviert und später, als sie verjährt waren, zu Mumienkartonage verarbeitet. Texte aus demselben Gerichtsarchiv sind publiziert in P.Heid. VIII und P.Köln XIV; weitere finden sich in der Papyrussammlung der Università degli Studi in Mailand. Die von der Papyrologin Bärbel Kramer (Universität Trier) mit Übersetzung und Kommentar herausgegebenen griechischen Texte werden zusammen mit den publizierten Parallelletexten von dem Rechtshistoriker C. M. Sánchez-Moreno Ellart (Universität Valencia) durch eine umfangreiche juristische Einleitung erschlossen. Damit werden von juristischer Seite zum ersten Mal anhand der neuen Papyri die Gemeinsamkeiten und Unterschiede des hellenistischen Prozessrechts gegenüber dem attischen Recht herausgearbeitet, soweit dieses in der griechischen Literatur, vor allem in den attischen Gerichtsreden und in Inschriften greifbar ist. 330 $aThe new court records from the Dikasterion in Heracleopolis include summons, witness testimonies and contracts dated to the beginning of the 2nd Century BC. The Greek papyri edited by B. Kramer are prefaced by an extensive juristic introduction by C. Sánchez-Moreno Ellart, stressing the similarities and differences between the Hellenistic and the Attic Law. 410 0$aArchiv fur Papyrusforschung und verwandte Gebiete. Beiheft ;$v36. 606 $aCivil procedure$zEgypt$vSources 606 $aLaw$zEgypt$vSources 606 $aEgyptian law 610 $aGreek papyrology. 610 $aHellenistic procedural law. 610 $aPtolemaic Egypt. 610 $atrial documents. 615 0$aCivil procedure 615 0$aLaw 615 0$aEgyptian law. 676 $a347.32 700 $aKramer$b Ba?rbel$0403045 702 $aEllart$b Carlos Ma. Sanchez-Moreno 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910828013103321 996 $aNeue Quellen zum Prozessrecht der Ptolemaerzeit$92695145 997 $aUNINA LEADER 13296nam 22007935 450 001 9910799216703321 005 20240828001754.0 010 $a981-9985-52-8 024 7 $a10.1007/978-981-99-8552-4 035 $a(CKB)29476347900041 035 $a(DE-He213)978-981-99-8552-4 035 $a(MiAaPQ)EBC31094237 035 $a(Au-PeEL)EBL31094237 035 $a(EXLCZ)9929476347900041 100 $a20231227d2024 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aPattern Recognition and Computer Vision $e6th Chinese Conference, PRCV 2023, Xiamen, China, October 13?15, 2023, Proceedings, Part XI /$fedited by Qingshan Liu, Hanzi Wang, Zhanyu Ma, Weishi Zheng, Hongbin Zha, Xilin Chen, Liang Wang, Rongrong Ji 205 $a1st ed. 2024. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2024. 215 $a1 online resource (XIV, 521 p. 207 illus., 202 illus. in color.) 225 1 $aLecture Notes in Computer Science,$x1611-3349 ;$v14435 311 08$a9789819985517 327 $aIntro -- Preface -- Organization -- Contents - Part XI -- Low-Level Vision and Image Processing -- Efficiently Amalgamated CNN-Transformer Network for Image Super-Resolution Reconstruction -- 1 Introduction -- 2 Related Work -- 2.1 CNN for SISR -- 2.2 Lightweight SISR -- 3 Method Overview -- 3.1 The Fundamentals of SISR -- 3.2 Network Structure -- 4 Experimental Results and Analysis -- 4.1 Training Details and Evaluation Metrics -- 4.2 Experimental Results and Analysis -- 5 Conclusion -- References -- A Hybrid Model for Video Compression Based on the Fusion of Feature Compression Framework and Multi-object Tracking Network -- 1 Introduction -- 2 Related Works -- 2.1 JDE (Joint Detection and Embedding Model) -- 2.2 DCT (Discrete Cosine Transform) Method -- 3 Methodology -- 3.1 Feature Extractor -- 3.2 Feature Reconstructor -- 3.3 Feature Encoder and Decoder -- 4 Experiment -- 4.1 The Architecture of the Hybrid Model -- 4.2 Training Details -- 4.3 Evaluation Results -- 5 Conclusions -- References -- Robust Degradation Representation via Efficient Diffusion Model for Blind Super-Resolution -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Lightweight Degradation Extractor (LDE) -- 3.2 Degradation-Aware Transformer (DAT) -- 3.3 Diffusion Model Training and Inference -- 4 Experiments -- 4.1 Training and Testing Datasets -- 4.2 Implementation and Training Details -- 4.3 Comparison with Existing Blind SR Methods -- 4.4 Ablation Study -- 5 Conclusion -- References -- MemDNet: Memorizing More Exogenous Information to Dehaze Natural Hazy Image -- 1 Introduction -- 2 Proposed Method -- 2.1 Dense Block -- 2.2 Enhanced Block -- 2.3 Memory Branch -- 3 Experiments -- 3.1 Experimental Settings -- 3.2 Comparison with SOTAs -- 3.3 Ablation Study -- 4 Conclusion -- References -- Technical Quality-Assisted Image Aesthetics Quality Assessment -- 1 Introduction. 327 $a2 Related Work -- 2.1 Technical Quality Assessment -- 2.2 Aesthetic Quality Assessment -- 3 Proposed Method -- 3.1 Theme-Aware Aesthetic Feature Extraction -- 3.2 Technical Quality Feature Extraction -- 3.3 Feature Fusion and Aesthetic Prediction -- 4 Experimental Results -- 4.1 Databases and Settings -- 4.2 Comparison with the State-of-the-Arts -- 4.3 Ablation Experiments -- 5 Conclusion -- References -- Self-supervised Low-Light Image Enhancement via Histogram Equalization Prior -- 1 Introduction -- 2 Methodology -- 2.1 Histogram Equalization Prior -- 2.2 Architecture -- 2.3 Loss Function -- 3 Experimental Validation -- 3.1 Implementation Details -- 3.2 Quantitative Evaluation -- 3.3 Qualitative Evaluation -- 3.4 Generalization Ability on Real-World Images -- 4 Ablation Studies -- 4.1 Comparison with Other Prior Information -- 4.2 The Effectiveness of Histogram Equalization Prior Loss -- 5 Conclusions -- References -- Enhancing GAN Compression by Image Probability Distribution Distillation -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Background -- 3.2 Image Probability Distribution Distillation -- 3.3 Asynchronous Weighted Discriminator -- 4 Experimentation -- 4.1 Experimental Settings -- 4.2 Result Comparison -- 4.3 Ablation Study -- 5 Conclusion -- References -- HDTR-Net: A Real-Time High-Definition Teeth Restoration Network for Arbitrary Talking Face Generation Methods -- 1 Introduction -- 2 Related Work -- 2.1 Talking Face Generation -- 2.2 Face Restoration -- 3 Method -- 3.1 Fine-Grained Feature Fusion -- 3.2 Decoder -- 3.3 Loss Function -- 4 Experiment -- 4.1 Experimental Settings -- 4.2 Experimental Results -- 4.3 Ablation Study -- 5 Conclusion -- References -- Multi-stream-Based Low-Latency Viewport Switching Scheme for Panoramic Videos -- 1 Introduction -- 2 Related Works -- 2.1 Tile-Based Viewport Adaptive Streaming. 327 $a2.2 MPEG-DASH and OMAF -- 2.3 MCTS Coding Scheme -- 3 Methodology -- 3.1 Tile-Based Panoramic Video Encoding -- 3.2 Multiple High Quality Streams -- 4 Experimental Results and Discussion -- 4.1 Experiment Setup -- 4.2 Analysis of the Results -- 5 Conclusion -- References -- Large Kernel Convolutional Attention Based U-Net Network for Inpainting Oracle Bone Inscription -- 1 Introduction -- 2 Method -- 2.1 Overview -- 2.2 Large Kernel Attention Block -- 2.3 U-Net Inpainting Generative Network -- 2.4 Global and Local Discriminative Networks -- 2.5 Loss Functions -- 3 Experimentation -- 3.1 Experimental Datasets and Settings -- 3.2 Evaluation Metrics -- 3.3 Experimental Results and Quantitative Evaluations -- 3.4 Ablation Study -- 4 Conclusion -- References -- L2DM: A Diffusion Model for Low-Light Image Enhancement -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Preliminaries -- 3.2 Autoencoder Module -- 3.3 ViTCondNet -- 3.4 Main Architecture -- 4 Experiments -- 4.1 Setup -- 4.2 Comparsion with SOTA Methods -- 4.3 Ablation Studies -- 5 Conclusion -- References -- Multi-domain Information Fusion for Key-Points Guided GAN Inversion -- 1 Introduction -- 2 Related Works -- 2.1 GAN Inversion -- 2.2 Latent Space Manipulation -- 3 Methodology -- 3.1 Overall Architecture -- 3.2 Unified Mapping Module -- 3.3 Multi Domain Information Fusion -- 3.4 Key-Point Patch Loss -- 3.5 Training Approaches for Inversion -- 4 Experiments -- 4.1 Implementation Details -- 4.2 Comparison with Inversion Method -- 4.3 Ablation Study and Analyse -- 5 Conclusion -- References -- Adaptive Low-Light Image Enhancement Optimization Framework with Algorithm Unrolling -- 1 Introduction -- 2 LIE Optimization Framework with Algorithm Unrolling -- 2.1 Unrolling LIE-QE Module -- 2.2 Loss of the LIE Optimization Framework -- 3 Experiment. 327 $a3.1 Evaluation of the Proposed Framework -- 3.2 Evaluation of Unrolling Decomposition Module -- 3.3 Comparison with Related Methods -- 4 Conclusion -- References -- Feature Matching in the Changed Environments for Visual Localization -- 1 Introduction -- 2 Related Work -- 2.1 Room Layout Estimation -- 2.2 Local Feature Matching -- 2.3 Datasets for Matching -- 3 Image Matching Dataset for Changed Indoor Environments -- 3.1 Design of the Dataset -- 3.2 Detailed Specifications -- 3.3 Obtaining Ground Truth Camera Pose -- 4 Method -- 4.1 Network Architecture -- 4.2 Loss Function -- 5 Experiment -- 5.1 Metrics and Datasets -- 5.2 Results -- 5.3 Implementation Details -- 6 Conclusion -- References -- To Be Critical: Self-calibrated Weakly Supervised Learning for Salient Object Detection -- 1 Introduction -- 2 Related Work -- 2.1 Salient Object Detection -- 2.2 Weakly Supervised Salient Object Detection -- 3 The Proposed Method -- 3.1 From Image-Level to Pixel-Level -- 3.2 Self-calibrated Training Strategy -- 3.3 Saliency Network -- 4 Dataset Construction -- 5 Experiments -- 5.1 Implementation Details -- 5.2 Datasets and Evaluation Metrics -- 5.3 Comparison with State-of-the-Arts -- 5.4 Ablation Studies -- 6 Conclusion -- References -- Image Visual Complexity Evaluation Based on Deep Ordinal Regression -- 1 Introduction -- 2 Related Work -- 2.1 Image Complexity Evaluation -- 2.2 Ordinal Regression -- 3 The Proposed Method -- 3.1 Improved the ICNet Model -- 3.2 Ordinal Regression Model -- 3.3 Total Loss Function -- 4 Experiment and Results -- 4.1 Dataset -- 4.2 Experimental Setup -- 4.3 Experimental Results Analysis -- 5 Conclusions -- References -- Low-Light Image Enhancement Based on Mutual Guidance Between Enhancing Strength and Image Appearance -- 1 Introduction -- 2 Related Works -- 3 Method -- 3.1 The Overall Framework of Our Model. 327 $a3.2 Mutual Guidance Module -- 3.3 Estimation of the Edge-Aware Lightness Map -- 4 Experiments -- 4.1 Experimental Settings -- 4.2 Experimental Results -- 4.3 Analysis of Our Method -- 5 Conclusion -- References -- Semantic-Guided Completion Network for Video Inpainting in Complex Urban Scene -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Problem Formulation -- 3.2 Semantic Video Completion Network -- 3.3 Video Synthesis Network -- 3.4 Loss Functions -- 4 Experiments -- 4.1 Benchmarks and Evaluation Metrics -- 4.2 Results and Discussion -- 4.3 Ablation Experiments -- 5 Conclusion -- References -- Anime Sketch Coloring Based on Self-attention Gate and Progressive PatchGAN -- 1 Introduction -- 2 Related Work -- 2.1 Style Transfer -- 2.2 Automatic Sketch Coloring -- 2.3 User-Guided Coloring -- 2.4 Reference-Based Sketch Image Coloring -- 3 Methodology -- 3.1 Overall Workflow -- 3.2 Self-attention Gate -- 3.3 Progressive PatchGAN -- 3.4 Loss Function -- 4 Experimental Results and Analysis -- 4.1 Implementation Details -- 4.2 Qualitative Evaluation -- 4.3 Quantitative Evaluation -- 4.4 Ablation Study -- 5 Conclusions -- References -- TransDDPM: Transformer-Based Denoising Diffusion Probabilistic Model for Image Restoration -- 1 Introduction -- 2 Related Work -- 2.1 Image Restoration -- 2.2 Denoising Diffusion Probabilistic Models -- 2.3 Diffusion Models for Image Restoration -- 3 Transformer-Based Denoising Diffusion Restoration Models -- 3.1 Overall Pipeline -- 3.2 Multi-Head Cross-Covariance Attention (MXCA) -- 3.3 Gated Feed-Forward Network (GFFN) -- 3.4 Accelerated with Implicit Sampling -- 4 Experiment -- 4.1 Datasets and Evaluation Metrics -- 4.2 Implementation Details -- 4.3 Image Deraining Experiments -- 4.4 Image Dehazing Experiments -- 4.5 Motion Deblurring Experiments -- 4.6 Ablation Experiment -- 4.7 Limitations -- 5 Conclusion. 327 $aReferences. 330 $aThe 13-volume set LNCS 14425-14437 constitutes the refereed proceedings of the 6th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2023, held in Xiamen, China, during October 13?15, 2023. The 532 full papers presented in these volumes were selected from 1420 submissions. The papers have been organized in the following topical sections: Action Recognition, Multi-Modal Information Processing, 3D Vision and Reconstruction, Character Recognition, Fundamental Theory of Computer Vision, Machine Learning, Vision Problems in Robotics, Autonomous Driving, Pattern Classification and Cluster Analysis, Performance Evaluation and Benchmarks, Remote Sensing Image Interpretation, Biometric Recognition, Face Recognition and Pose Recognition, Structural Pattern Recognition, Computational Photography, Sensing and Display Technology, Video Analysis and Understanding, Vision Applications and Systems, Document Analysis and Recognition, Feature Extraction and Feature Selection, Multimedia Analysis and Reasoning, Optimization and Learning methods, Neural Network and Deep Learning, Low-Level Vision and Image Processing, Object Detection, Tracking and Identification, Medical Image Processing and Analysis. . 410 0$aLecture Notes in Computer Science,$x1611-3349 ;$v14435 606 $aImage processing$xDigital techniques 606 $aComputer vision 606 $aArtificial intelligence 606 $aApplication software 606 $aComputer networks 606 $aComputer systems 606 $aMachine learning 606 $aComputer Imaging, Vision, Pattern Recognition and Graphics 606 $aArtificial Intelligence 606 $aComputer and Information Systems Applications 606 $aComputer Communication Networks 606 $aComputer System Implementation 606 $aMachine Learning 615 0$aImage processing$xDigital techniques. 615 0$aComputer vision. 615 0$aArtificial intelligence. 615 0$aApplication software. 615 0$aComputer networks. 615 0$aComputer systems. 615 0$aMachine learning. 615 14$aComputer Imaging, Vision, Pattern Recognition and Graphics. 615 24$aArtificial Intelligence. 615 24$aComputer and Information Systems Applications. 615 24$aComputer Communication Networks. 615 24$aComputer System Implementation. 615 24$aMachine Learning. 676 $a929.605 702 $aLiu$b Qingshan$f-1952, 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910799216703321 996 $aPattern recognition and computer vision$91972598 997 $aUNINA