LEADER 06973nam 2200565 450 001 996464525103316 005 20220227151733.0 010 $a3-030-92273-1 024 7 $a10.1007/978-3-030-92273-3 035 $a(CKB)5100000000152615 035 $a(MiAaPQ)EBC6857544 035 $a(Au-PeEL)EBL6857544 035 $a(DE-He213)978-3-030-92273-3 035 $a(OCoLC)1289372762 035 $a(BIP)082129312 035 $a(PPN)25938495X 035 $a(EXLCZ)995100000000152615 100 $a20220227d2021 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aNeural information processing $e28th International Conference, ICONIP 2021, Sanur, Bali, Indonesia, December 8-12, 2021, Proceedings, Part IV. /$fTeddy Mantoro [and four others], editors 205 $a1st ed. 2021. 210 1$aCham, Switzerland :$cSpringer,$d[2021] 210 4$d2021 215 $a1 online resource (718 pages) 225 1 $aTheoretical Computer Science and General Issues,$x2512-2029 ;$v13111 311 $a3-030-92272-3 320 $aIncludes bibliographical references and index. 327 $aApplications -- Deep Supervised Hashing By Classification For Image Retrieval -- Towards Human-level Performance in Solving Double Dummy Bridge Problem -- Coarse-to-Fine Visual Place Recognition -- BFConv: Improving Convolutional Neural Networks with Butterfly Convolution -- Integrating Rich Utterance Features for Emotion Recognition in Multi-party Conversations -- Vehicle Image Generation Going Well with the Surroundings -- Scale Invariant Domain Generalization Image Recapture Detection -- Tile2Vec with Predicting Noise for Land Cover Classification -- A Joint Representation Learning Approach for Social Media Tag Recommendation -- Identity-based Data Augmentation via Progressive Sampling for One-Shot Person Re-identification -- Feature Fusion Learning Based on LSTM and CNN Networks for Trend Analysis of Limit Order Books -- WikiFlash: Generating Flashcards from Wikipedia Articles -- Video Face Recognition with Audio-Visual Aggregation Network -- WaveFuse: A Unified Unsupervised Framework for Image Fusion with Discrete Wavelet Transform -- Manipulation-invariant Fingerprints for Cross-dataset Deepfake Detection -- Low-resource Neural Machine Translation Using Fast Meta-Learning method -- Efficient, Low-Cost, Real-Time Video Super-Resolution Network -- On the Unreasonable Effectiveness of Centroids in Image Retrieval -- Few-shot Classification with Multi-task Self-supervised Learning -- Self-Supervised Compressed Video Action Recognition via Temporal-Consistent Sampling -- Stack-VAE network for Zero-Shot Learning -- TRUFM: a Transformer-guided Framework for Fine-grained Urban Flow Inference -- Saliency Detection Framework Based on Deep Enhanced Attention Network -- SynthTriplet GAN: Synthetic Query Expansion for Multimodal Retrieval -- SS-CCN: Scale Self-guided Crowd Counting Network -- QS-Hyper: A Quality-Sensitive Hyper Network for the No-Reference Image Quality Assessment -- An Efficient Manifold Density Estimator for All Recommendation Systems -- Cleora: A Simple, Strong and Scalable Graph Embedding Scheme -- STA3DCNN: Spatial-temporal Attention 3D Convolutional Neural Network for Citywide Crowd Flow Prediction -- Learning Pre-Grasp Pushing Manipulation of Wide and Flat Objects using Binary Masks -- Multi-DIP: A General Framework For Unsupervised Multi-degraded Image Restoration -- Multi-Attention Network for Arbitrary Style Transfer -- Image Brightness Adjustment with Unpaired Training -- Self-Supervised Image-to-Text and Text-to-Image Synthesis -- TextCut: A Multi-region Replacement Data Augmentation Approach for Text Imbalance Classification -- A Multi-task Model for Sentiment aided Cyberbullying Detection in Code-Mixed Indian Languages -- A Transformer-based Model for Low-resource Event Detection -- Malicious Domain Detection on Imbalanced Data with Deep Reinforcement Learning -- Designing and Searching for Lightweight Monocular Depth Network -- Improving Question Answering over Knowledge Graphs Using Graph Summarization -- Multi-Stage Hybrid Attentive Networks for Knowledge-Driven Stock Movement Prediction -- End-to-End Edge Detection via Improved Transformer Model -- Isn?t it ironic, don?t you think -- Neural Local and Global Contexts Learning for Word Sense Disambiguation -- Towards Better Dermoscopic Image Feature Representation Learning for Melanoma Classification -- Paraphrase Identification with Neural Elaboration Relation Learning -- Hybrid DE-MLP-based Modeling Technique for Prediction of Alloying Element Proportions and Process Parameters -- A Mutual Information-based Disentanglement Framework for Cross-Modal Retrieval -- AGRP:A Fused Aspect-Graph Neural Network for Rating Prediction -- Classmates Enhanced Diversity-self-attention Network for Dropout Prediction in MOOCs -- A Hierarchical Graph-based Neural Network for Malware Classification -- A Visual Feature Detection Algorithm Inspired by Spatio-temporal Properties of Visual Neurons -- Knowledge Distillation Method for Surface Defect Detection -- Adaptive Selection of Classifiers for Person Recognition by Iris Pattern and Periocular Image -- Multi-Perspective Interactive Model for Chinese Sentence Semantic Matching -- An Effective Implicit Multi-Interest Interaction Network for Recommendation. 330 $aThe four-volume proceedings LNCS 13108, 13109, 13110, and 13111 constitutes the proceedings of the 28th International Conference on Neural Information Processing, ICONIP 2021, which was held during December 8-12, 2021. The conference was planned to take place in Bali, Indonesia but changed to an online format due to the COVID-19 pandemic. The total of 226 full papers presented in these proceedings was carefully reviewed and selected from 1093 submissions. The papers were organized in topical sections as follows: Part I: Theory and algorithms; Part II: Theory and algorithms; human centred computing; AI and cybersecurity; Part III: Cognitive neurosciences; reliable, robust, and secure machine learning algorithms; theory and applications of natural computing paradigms; advances in deep and shallow machine learning algorithms for biomedical data and imaging; applications; Part IV: Applications. 410 0$aLecture notes in computer science ;$v13111. 517 3 $aICONIP 2021 606 $aNeural networks (Computer science)$vCongresses 615 0$aNeural networks (Computer science) 676 $a006.32 702 $aMantoro$b Teddy$4edt 702 $aLee$b Minho$4edt 702 $aAyu$b Media Anugerah$4edt 702 $aHidayanto$b Achmad Nizar$4edt 702 $aWong$b Kok Wai$4edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996464525103316 996 $aNeural Information Processing$92554499 997 $aUNISA LEADER 03440nam 2200601 450 001 9910790825103321 005 20230120011200.0 010 $a1-84334-518-8 010 $a1-78063-032-8 035 $a(CKB)2550000001169855 035 $a(EBL)1584429 035 $a(OCoLC)866858709 035 $a(SSID)ssj0000704140 035 $a(PQKBManifestationID)11419942 035 $a(PQKBTitleCode)TC0000704140 035 $a(PQKBWorkID)10692985 035 $a(PQKB)10078405 035 $a(Au-PeEL)EBL1584429 035 $a(CaPaEBR)ebr10821072 035 $a(CaONFJC)MIL551840 035 $a(CaSebORM)9781843345183 035 $a(MiAaPQ)EBC1584429 035 $a(EXLCZ)992550000001169855 100 $a20100526d2010 uy| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aAbstracts and abstracting $ea genre and set of skills for the twenty-first century /$fTibor Koltay 205 $a1st edition 210 1$aOxford :$cChandos Pub.,$d2010. 215 $a1 online resource (237 p.) 225 0$aChandos information professional series 300 $aDescription based upon print version of record. 311 $a1-84334-517-X 311 $a1-306-20589-1 320 $aIncludes bibliographical references (pages 203-223) and index. 327 $aCover; Abstracts and Abstracting: A genre and set of skills for the twenty-first century; Copyright; Contents; About the author; 1 Introduction; Who is this book for?; What is abstracting and what is an abstract?; Why abstracts and abstracting?; The structure of the book; 2 Definitions; The abstract; The original; Related concepts and genres; 3 The characteristics of the abstract; The length; Functions; Types of abstract; The objectivity of the abstract; The author abstract; 4 What does an abstractor have to know?; Who can be an abstractor?; The knowledge base of the abstractor 327 $aProfessional summarisationThe information literacy context; Abstracting education; The rewards of abstracting; 5 The practice of abstracting: structure, processes and language; The structure of abstracts; The process made simple; The language; Reflections on the abstracting process; How to evaluate abstracts; 6 The practice of abstracting: examples; Examples of abstract writing; Example 1; Example 2; 7 Beyond language and style; Approaches and models; Abstracting and comprehension; 8 Conclusion; References; Index 330 $aDespite their changing role, abstracts remain useful in the digital world. Highly beneficial to information professionals and researchers who work and publish in different fields, this book summarizes the most important and up-to-date theory of abstracting, as well as giving advice and examples for the practice of writing different kinds of abstracts. The book discusses the length, the functions and basic structure of abstracts, outlining a new approach to informative and indicative abstracts. The abstractors' personality, their linguistic and non-linguistic knowledge and skills are also discu 410 0$aChandos Information Professional Series 606 $aAbstracting 615 0$aAbstracting. 676 $a025.41 700 $aKoltay$b Tibor$0988129 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910790825103321 996 $aAbstracts and abstracting$93697804 997 $aUNINA LEADER 01565nas 2200445- 450 001 996353849603316 005 20240204213017.0 011 $a2522-400X 035 $a(DE-599)ZDB3072323-1 035 $a(OCoLC)1202536730 035 $a(CKB)4100000008380712 035 $a(CONSER)--2021221606 035 $a(EXLCZ)994100000008380712 100 $a20201011a19979999 s-- - 101 0 $aukr 135 $aur|n||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aProblemy suchasnoho literaturoznavstva 210 1$aOdesa, Ukraïna :$cOdes?ky? nat?sional?ny? universytet im. I.I. Mechnykova 215 $a1 online resource 300 $aRefereed/Peer-reviewed 311 $a2312-6809 517 1 $aProblems of contemporary literary studies 606 $aUkrainian literature$xHistory and criticism$vPeriodicals 606 $aRussian literature$xHistory and criticism$vPeriodicals 606 $aUkrainian literature$2fast$3(OCoLC)fst01160526 606 $aRussian literature$2fast$3(OCoLC)fst01102312 608 $aCriticism, interpretation, etc.$2fast 608 $aPeriodicals.$2fast 615 0$aUkrainian literature$xHistory and criticism 615 0$aRussian literature$xHistory and criticism 615 7$aUkrainian literature. 615 7$aRussian literature. 712 02$aOdes?ky? nat?sional?ny? universytet im. I.I. Mechnykova, 906 $aJOURNAL 912 $a996353849603316 996 $aProblemy suchasnoho literaturoznavstva$92551542 997 $aUNISA