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1. |
Record Nr. |
UNINA9910828547203321 |
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Autore |
Walters Mark Jerome |
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Titolo |
Florida scrub jay : field notes on a vanishing bird / / Mark Jerome Walters |
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Pubbl/distr/stampa |
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Gainesville, Florida : , : University Press of Florida, , [2021] |
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©2021 |
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Descrizione fisica |
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1 online resource (130 pages) : illustrations |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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2. |
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UNISA996546841303316 |
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Autore |
Hewage Chaminda |
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Titolo |
Data Protection in a Post-Pandemic Society [[electronic resource] ] : Laws, Regulations, Best Practices and Recent Solutions / / edited by Chaminda Hewage, Yogachandran Rahulamathavan, Deepthi Ratnayake |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 |
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ISBN |
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Edizione |
[1st ed. 2023.] |
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Descrizione fisica |
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1 online resource (246 pages) |
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Altri autori (Persone) |
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RahulamathavanYogachandran |
RatnayakeDeepthi |
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Disciplina |
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Soggetti |
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Data protection—Law and legislation |
Data protection |
Financial risk management |
Privacy |
Data and Information Security |
Risk Management |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Chapter. 1. Post-Covid-19 Metaverse Cybersecurity and Data Privacy-Present and Future Challenges -- Chapter. 2. Keeping it Low-Key: Modern-day approaches to Privacy-Preserving Machine Learning -- Chapter. 3. Security Analysis of Android Hot Cryptocurrency Wallet Applications -- Chapter. 4. Exploring the Opportunities of Applying Digital Twins for Intrusion Detection in Industrial Control Systems of Production and Manufacturing – A Systematic Review -- Chapter. 5. Securing Privacy During a World Health Emergency: Exploring How to Create a Balance Between the Need to Save the World and People’s Right to Privacy -- Chapter. 6. Federated Learning: Data privacy and cyber security in edge-based machine learning Mobile Malware Detection Using Consortium -- Chapter. 7. Emerging Computer Security Laws and Regulations across the Globe: A Comparison between Sri Lankan and Contemporary International Computer Acts -- Chapter. |
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8. Legal Considerations and Ethical Challenges of Artificial Intelligence on Internet of Things and Smart Cities. |
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Sommario/riassunto |
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This book offers the latest research results and predictions in data protection with a special focus on post-pandemic society. This book also includes various case studies and applications on data protection. It includes the Internet of Things (IoT), smart cities, federated learning, Metaverse, cryptography and cybersecurity. Data protection has burst onto the computer security scene due to the increased interest in securing personal data. Data protection is a key aspect of information security where personal and business data need to be protected from unauthorized access and modification. The stolen personal information has been used for many purposes such as ransom, bullying and identity theft. Due to the wider usage of the Internet and social media applications, people make themselves vulnerable by sharing personal data. This book discusses the challenges associated with personal data protection prior, during and post COVID-19 pandemic. Some of these challenges are caused by the technological advancements (e.g., Artificial Intelligence (AI)/Machine Learning (ML) and ChatGPT). In order to preserve the privacy of the data involved, there are novel techniques such as zero knowledge proof, fully homomorphic encryption, multi-party computations are being deployed. The tension between data privacy and data utility drive innovation in this area where numerous start-ups around the world have started receiving funding from government agencies and venture capitalists. This fuels the adoption of privacy-preserving data computation techniques in real application and the field is rapidly evolving. Researchers and students studying/working in data protection and related security fields will find this book useful as a reference. . |
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3. |
Record Nr. |
UNINA9910983328503321 |
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Titolo |
Pattern Recognition and Computer Vision : 7th Chinese Conference, PRCV 2024, Urumqi, China, October 18–20, 2024, Proceedings, Part VII / / edited by Zhouchen Lin, Ming-Ming Cheng, Ran He, Kurban Ubul, Wushouer Silamu, Hongbin Zha, Jie Zhou, Cheng-Lin Liu |
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Pubbl/distr/stampa |
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Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025 |
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ISBN |
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Edizione |
[1st ed. 2025.] |
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Descrizione fisica |
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1 online resource (XIV, 587 p. 203 illus., 182 illus. in color.) |
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Collana |
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Lecture Notes in Computer Science, , 1611-3349 ; ; 15037 |
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Disciplina |
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Image processing - Digital techniques |
Computer vision |
Artificial intelligence |
Application software |
Computer networks |
Computer systems |
Machine learning |
Computer Imaging, Vision, Pattern Recognition and Graphics |
Artificial Intelligence |
Computer and Information Systems Applications |
Computer Communication Networks |
Computer System Implementation |
Machine Learning |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Scene Text Recognition via k-NN Attention-based Decoder and Margin-based Softmax LossReal-Time Text Detection with Multi-Level Feature Fusion and Pixel ClusteringREFINED AND LOCALITY-ENHANCED FEATURE FOR HANDWRITTEN MATHEMATICAL EXPRESSION RECOGNITIONLearning Fine-grained and Semantically Aware Mamba Representations for Tampered Text Detection in ImagesDual Feature Enhanced Scene Text Recognition Method for Low-Resource UyghurSegmentation-free Todo Mongolian OCR and Its Public |
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DatasetHybrid Encoding Method for Scene Text Recognition in Low-Resource UyghurROBC: a Radical-Level Oracle Bone Character DatasetIntegrated Recognition of Arbitrary-Oriented Multi-Line Billet NumberImproving Scene Text Recognition with Counting Aware Contrastive Learning and Attention AlignmentGridMask: An Efficient Scheme for Real Time Curved Scene Text DetectionTibetan Handwriting Recognition Method based on Structural Re-parameterization ViT and Vertical AttentionMFH: Marrying Frequency Domain with Handwritten Mathematical Expression RecognitionLeveraging Structure Knowledge and Deep Models for the Detection of Abnormal Handwritten Text -- OCR-aware Scene Graph Generation via Multi-modal Object Representation Enhancement and Logical Bias Learning -- Enhancing Transformer-based Table Structure Recognition for Long Tables -- Show Exemplars and Tell Me What You See: In-context Learning with Frozen Large Language Models for Text -- VQAMLR-NET: an arbitrary skew angle detection algorithm for complex layout document images -- TextViTCNN： Enhancing Natural Scene Text Recognition with Hybrid Transformer and Convolutional NetworksEnhancing Visual Information Extraction with Large Language Models through Layout-aware Instruction Tuning -- SFENet: Arbitrary Shapes Scene Text Detection with Semantic Feature ExtractorImproving Zero-Shot Image Captioning Efficiency with Metropolis-Hastings Sampling -- Improving Text Classification Performance through Multimodal Representation -- A Multi-feature Fusion Approach for Words Recognition of Ancient Mongolian Documents -- TableRocket: An Efficient and Effective Framework for Table Reconstruction -- Not All Texts Are the Same: Dynamically Querying Texts for Scene Text Detection -- Multi-Modal Attention based on 2D Structured Sequence for Table Recognition -- A Two-stream Hybrid CNN-Transformer Network for Skeleton-based Human Interaction Recognition -- Skeleton-Language Pre-training to Collaborate with Self-Supervised Human Action Recognition -- Spatio-Temporal Contrastive Learning for Compositional Action RecognitionPath-Guided Motion Prediction with Multi-View Scene Perception -- Privacy-preserving Action Recognition: A Survey -- Attention-based Spatio-temporal modeling with 3D Convolutional Neural Networks for Dynamic Gesture Recognition -- MIT: Multi-cue Injected Transformer for Two-stage HOI Detection -- DIDA: Dynamic Individual-to-integrated Augmentation for Self-Supervised Skeleton-Based Action Recognition -- Multi-scale Spatial and Temporal Feature Aggregation Graph Convolutional Network for Skeleton-Based Action Recognition -- Improving Video Representation of Vision-Language Model with Decoupled Explicit Temporal Modeling -- KS-FuseNet: An efficient action recognition method based on keyframe selection and feature fusion -- Dynamic Skeleton Association Transformer for dyadic Interaction Action RecognitionSpecies-Aware Guidance for Animal Action Recognition with Vision-Language Knowledge. |
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Sommario/riassunto |
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This 15-volume set LNCS 15031-15045 constitutes the refereed proceedings of the 7th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2024, held in Urumqi, China, during October 18–20, 2024. The 579 full papers presented were carefully reviewed and selected from 1526 submissions. The papers cover various topics in the broad areas of pattern recognition and computer vision, including machine learning, pattern classification and cluster analysis, neural network and deep learning, low-level vision and image processing, object detection and recognition, 3D vision and reconstruction, action recognition, video analysis and understanding, document analysis and recognition, biometrics, medical image analysis, and various applications. |
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