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[null,"1.","Record Nr.",null,"UNINA9910454060003321"]
[null,null,"Autore",null,"Williams Anne <1947->"]
[null,null,"Titolo",null,"Art of darkness [[electronic resource] ] : a poetics of Gothic / / Anne Williams"]
[null,null,"Pubbl/distr/stampa",null,"Chicago, : University of Chicago Press, 1995"]
[null,null,"ISBN",null,"1-282-07027-4"]
[{"$nulls":4},"9786612070273"]
[{"$nulls":4},"0-226-89903-9"]
[null,null,"Descrizione fisica",null,"1 online resource (325 p.)"]
[null,null,"Disciplina",null,"823/.0872909"]
[null,null,"Soggetti",null,"English literature - 18th century - History and criticism - Theory, etc"]
[{"$nulls":4},"English literature - 19th century - History and criticism - Theory, etc"]
[{"$nulls":4},"Horror tales, English - History and criticism - Theory, etc"]
[{"$nulls":4},"Gothic revival (Literature) - Great Britain"]
[{"$nulls":4},"Romanticism - Great Britain"]
[{"$nulls":4},"Poetics"]
[{"$nulls":4},"Electronic books."]
[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 (p. 285-300) and index."]
[null,null,"Nota di contenuto",null,"Frontmatter -- CONTENTS -- ACKNOWLEDGMENTS -- INTRODUCTION. Gothic Fiction's Family Romances -- Part One. Riding Nightmares; or, What's Novel about Gothic? -- Part Two. Reading Nightmeres; or, The Two Gothic Traditions -- EPILOGUE. The Mysteries of Enlightenment; or Dr. Freud's Gothic Novel -- APPENDIX A. Inner and Outer Spaced The Alien Trilogy -- APPENDIX B. Gothic Families -- APPENDIX C. The Female Plot of Ghotic Fiction -- Notes -- Bibliography -- Index"]
[null,null,null,"Sommario/riassunto","Art of Darkness is an ambitious attempt to describe the principles governing Gothic literature. Ranging across five centuries of fiction, drama, and verse-including tales as diverse as Horace Walpole's The Castle of Otranto, Shelley's Frankenstein, Coleridge's The Rime of the Ancient Mariner, and Freud's The Mysteries of Enlightenment-Anne Williams proposes three new premises: that Gothic is \"poetic,\" not novelistic, in nature; that there are two parallel Gothic traditions, Male and Female; and that the Gothic and the Romantic represent a single literary tradition. Building on the psychoanalytic and feminist theory of Julia Kristeva, Williams argues that Gothic conventions such as the "]
[{"$nulls":4},"haunted castle and the family curse signify the fall of the patriarchal family; Gothic is therefore \"poetic\" in Kristeva's sense because it reveals those \"others\" most often identified with the female. Williams identifies distinct Male and Female Gothic traditions: In the Male plot, the protagonist faces a cruel, violent, and supernatural world, without hope of salvation. The Female plot, by contrast, asserts the power of the mind to comprehend a world which, though mysterious, is ultimately sensible. By showing how Coleridge and Keats used both Male and Female Gothic, Williams challenges accepted notions about gender and authorship among the Romantics. Lucidly and gracefully written, Art of Darkness alters our understanding of the Gothic tradition, of Romanticism, and of the relations between gender and genre in literary history."]
[null,"2.","Record Nr.",null,"UNISA996565867203316"]
[null,null,"Autore",null,"Bebis George"]
[null,null,"Titolo",null,"Advances in Visual Computing : 18th International Symposium, ISVC 2023, Lake Tahoe, NV, USA, October 16-18, 2023, Proceedings, Part I"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer, , 2024"]
[{"$nulls":4},"©2023"]
[null,null,"ISBN",null,"3-031-47969-6"]
[null,null,"Edizione",null,"[1st ed.]"]
[null,null,"Descrizione fisica",null,"1 online resource (630 pages)"]
[null,null,"Collana",null,"Lecture Notes in Computer Science Series ; ; v.14361"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Intro -- Preface -- Organization -- Keynote Talks -- Machine Learning for Scientific Data Analysis and Visualization -- Estimating the Structure and Motion of Biomolecules at Atomic Resolutions -- Curriculum Learning and Active Learning, for Visual Object Recognition when Data is Scarce -- Have We Solved Image Correspondences? -- Visual Content Manipulation by Learning Generative Models -- Lights, Camera, Animation! Adaptive Simulation Methods for Training and Entertainment -- Beyond the Specs: A Computational and Human-Centered Approach to Wearability in AR/VR -- Contents - Part I -- Contents - Part II -- ST: Biomedical Image Analysis Techniques for Cancer Detection, Diagnosis and Management -- Hybrid Region and Pixel-Level Adaptive Loss for Mass Segmentation on Whole Mammography Images -- 1 Introduction -- 2 Related Work -- 2.1 Mass Segmentation on Whole Mammograms -- 2.2 Loss for Medical Image Segmentation -- 3 Methodology -- 3.1 Hybrid Pixel-Level Loss -- 3.2 Hybrid Region-Level Loss -- 3.3 Density-Adaptive Sample-Level Prioritizing Loss -- 4 Experimental Results -- 4.1 Datasets -- 4.2 Evaluation Metrics -- 4.3 Comparison with State-of-the-Art Methods -- 5 Conclusion -- References -- Deep Learning Based GABA Edited-MRS Signal Reconstruction -- 1 Introduction -- 2 Methods -- 2.1 Dataset -- 2.2 J-Difference Spectrum -- 2.3 Dual Branch Self-Attention Neural Network -- 2.4 Evaluation Metrics -- 3 Results and Discussion -- 4 Conclusion -- References -- Investigating the Impact of Attention on Mammogram Classification -- 1 Introduction -- 2 Data and Methods -- 2.1 Data Selection and Preprocessing -- 2.2 Selection of Models -- 2.3 Selection of Attention Methods -- 2.4 Training and "]
[{"$nulls":4},"Testing Process -- 3 Results and Discussion -- 3.1 Impact of Attention on CNN Performance -- 3.2 Impact of Model Architecture on Performance Differences."]
[{"$nulls":4},"3.3 Impact of Attention on Resolution -- 3.4 Impact of Attention on Abnormality Type -- 3.5 Relationship Between Model Activation and AU-ROC -- 4 Conclusions -- References -- ReFit: A Framework for Refinement of Weakly Supervised Semantic Segmentation Using Object Border Fitting for Medical Images -- 1 Introduction -- 2 Our ReFit Framework -- 2.1 Unsupervised Segment Detection -- 2.2 Class Activation Map - CAM -- 2.3 The BoundaryFit Module -- 3 Results and Discussion -- 3.1 Ablation Studies -- 4 Conclusion -- References -- A Data-Centric Approach for Pectoral Muscle Deep Learning Segmentation Enhancements in Mammography Images -- 1 Introduction -- 2 Related Work -- 3 Mammography Segmentation -- 3.1 Dataset -- 3.2 Model Training -- 3.3 Drawbacks -- 4 Data-Centric Model Optimization -- 4.1 Stage I: Annotation Correction -- 4.2 Stage II: Downsampling -- 5 Results -- 5.1 Evaluation Metrics -- 5.2 Evaluated Training Datasets -- 5.3 Intersection over Union Evaluation -- 5.4 Classification Metrics for Pectoral Muscle Detection in CC View -- 6 Conclusion -- References -- Visualization -- Visualizing Multimodal Time Series at Scale -- 1 Introduction -- 2 Related Work -- 3 Overview Scenario -- 4 Detail Methods and Implementation -- 4.1 Time Series Dataset -- 4.2 Exploiting Elasticsearch for Fast Search and Big Query -- 4.3 Visualizing Time Series -- 5 Exploring UMAFall Dataset with TimeXplore -- 6 Conclusions and Future Work -- References -- Hybrid Tree Visualizations for Analysis of Gerrymandering -- 1 Introduction -- 2 Related Work -- 3 Gerrymandering -- 4 Data Model in Gerrymandering -- 5 Visual Design -- 6 Analysis Examples -- 6.1 Evaluating the Efficiency Gap -- 6.2 Assessing Electoral Competition -- 7 Conclusion -- References -- ArcheryVis: A Tool for Analyzing and Visualizing Archery Performance Data -- 1 Introduction -- 2 Related Work."]
[{"$nulls":4},"2.1 Archery Performance Analysis -- 2.2 Archery Scoring Apps -- 3 Data Collection, Processing, and Analysis -- 3.1 Data Collection -- 3.2 Ring and Center Detection -- 3.3 Shot Detection and Calibration -- 3.4 Scoring and Statistical Measures -- 4 Visual Interface and Interaction -- 5 Results and Discussion -- 5.1 Brushing and Filtering -- 5.2 Trainee Comparison -- 5.3 Statistical Measure as Performance Indicator -- 5.4 Empirical Evaluation -- 5.5 Limitations -- 6 Conclusions and Future Work -- References -- Spiro: Order-Preserving Visualization in High Performance Computing Monitoring -- 1 Introduction -- 2 Related Work -- 2.1 Spiral Layout in Visualization -- 2.2 Monitoring with Spiral Layout -- 3 Monitoring Tasks -- 4 Spiro Design -- 4.1 Design Rationales -- 4.2 Visual Encoding -- 5 Case Studies -- 5.1 Clustering on Compute Servers -- 5.2 Exploring Usage Behavior -- 6 Conclusion and Future Work -- References -- From Faces to Volumes - Measuring Volumetric Asymmetry in 3D Facial Palsy Scans -- 1 Introduction -- 2 Related Work -- 3 Data Acquisition -- 4 Methods -- 4.1 3D Landmark Extraction for Facial Palsy Patients -- 4.2 Radial Curves -- 4.3 Lateral Face Mesh Generation -- 4.4 Volume Estimation for Lateral Face Sides -- 4.5 Volumetric Difference Visualization -- 5 Volume Analysis During Dynamic Movements -- 6 Conclusions and Future Work -- References -- Video Analysis and Event Recognition -- Comparison of Autoencoder Models for Unsupervised Representation Learning of Skeleton Sequences -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Proposed Methods -- 4 Experiments -- 4.1 Datasets -- 4.2 Results Analysis and Comparisons -- 5 Conclusion and Future Works -- References -- Local and Global Context Reasoning for Spatio-"]
[{"$nulls":4},"Temporal Action Localization -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 3.1 Overall Pipeline."]
[{"$nulls":4},"3.2 Near-Actor Relation Network -- 4 Experiments on JHMDB21 -- 4.1 Implementation Details -- 4.2 Comparison on JHMDB21 -- 4.3 Ablation Study -- 4.4 Qualitative Results -- 5 Experiments on AVA -- 5.1 Implementation Details -- 5.2 Comparison on AVA -- 6 Conclusion -- References -- Zero-Shot Video Moment Retrieval Using BLIP-Based Models -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Computing Image and Text Embeddings -- 3.2 Sparse Frame-Sampling Strategies -- 3.3 Moment-Query Matching -- 4 Experiments -- 5 Results and Discussion -- 6 Conclusions and Future Work -- References -- Self-supervised Representation Learning for Fine Grained Human Hand Action Recognition in Industrial Assembly Lines -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Model Architecture -- 3.2 Masking Method -- 4 Experiments -- 4.1 Datasets -- 4.2 Model Training Environment -- 4.3 Self-supervised Pretraining and Downstream Task -- 5 Results and Analysis -- 5.1 Results Self-supervised Learning -- 5.2 Results Downstream Task -- 5.3 Analysis -- 6 Conclusion and Outlook -- References -- ST: Innovations in Computer Vision &amp -- Machine Learning for Critical &amp -- Civil Infrastructures -- Pretext Tasks in Bridge Defect Segmentation Within a ViT-Adapter Framework -- 1 Introduction -- 2 Methods -- 2.1 ViT-Adapter Model -- 2.2 Datasets -- 2.3 Supervised Learning (SL) Pre-training -- 2.4 Self- And Semi-Supervised Learning (SSL) Pre-training -- 2.5 Training Parameters -- 3 Results and Discussion -- 4 Conclusion -- References -- A Few-Shot Attention Recurrent Residual U-Net for Crack Segmentation -- 1 Introduction -- 1.1 Current Limitations and Our Contribution -- 2 Proposed Architecture -- 2.1 R2AU-Net Architecture for Road Crack Segmentation -- 2.2 Few-Shot Learning for Segmentation Refinement -- 3 Experimental Setup and Results -- 3.1 Dataset Description."]
[{"$nulls":4},"3.2 Comparative Algorithms and Training Configuration -- 3.3 Experiments and Comparisons -- 4 Conclusions -- References -- Efficient Resource Provisioning in Critical Infrastructures Based on Multi-Agent Rollout Enabled by Deep Q-Learning -- 1 Introduction -- 2 Related Work -- 3 Workload Management in Critical Infrastructures -- 3.1 Infrastructure Model -- 3.2 Problem Formulation -- 3.3 Deterministic Markov Decision Process Model -- 3.4 Multi-Agent Rollout Enabled by Deep Q-Learning -- 4 Simulation Experiments -- 4.1 Experimental Setup -- 4.2 Evaluation Results -- 5 Conclusions -- References -- Video-Based Recognition of Aquatic Invasive Species Larvae Using Attention-LSTM Transformer -- 1 Introduction -- 1.1 Attention-LSTM -- 2 Related Work -- 3 Proposed Method -- 3.1 Model Architecture -- 3.2 Attention-LSTM Layer -- 3.3 Model Variations -- 4 Invasive Species Dataset -- 5 Empirical Evaluation -- 6 Conclusion -- References -- ST: Generalization in Visual Machine Learning -- Latent Space Navigation for Face Privacy: A Case Study on the MNIST Dataset -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 4 Experimental Result -- 5 Future Work -- 6 Conclusion -- References -- Domain Generalization for Foreground Segmentation Using Federated Learning -- 1 Introduction -- 2 Related Work -- 3 Proposed Work -- 3.1 Model Architecture -- 3.2 Training Technique -- 4 Experiments -- 4.1 Datasets -- 4.2 Implementation Details -- 4.3 Traditional Foreground Segmentation Experiment -- 4.4 Domain Generalization Experiment -- 4.5 Few-Shot Experiment -- 5 Conclusion and Future Work -- References -- Probabilistic Local Equivalence Certification for Robustness Evaluation -- 1 Introduction -- 2 Related Work -- 3 Probabilistic Local Equivalence Certification -- 3.1 Probabilistic Local "]
[{"$nulls":4},"Equivalence Certification -- 3.2 When Labels are Available."]
[{"$nulls":4},"3.3 The Case of Classification."]