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001434674 001__ 1434674
001434674 003__ OCoLC
001434674 005__ 20230309003813.0
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001434674 008__ 210224s2021\\\\sz\a\\\\o\\\\\101\0\eng\d
001434674 019__ $$a1240586720$$a1249944599
001434674 020__ $$a9783030687809$$q(electronic bk.)
001434674 020__ $$a3030687805$$q(electronic bk.)
001434674 020__ $$z9783030687793
001434674 0247_ $$a10.1007/978-3-030-68780-9$$2doi
001434674 035__ $$aSP(OCoLC)1241066415
001434674 040__ $$aDKU$$beng$$erda$$epn$$cDKU$$dOCLCO$$dGZM$$dGW5XE$$dEBLCP$$dOCLCO$$dOCLCF$$dLEATE$$dUKAHL$$dDKU$$dOCLCQ$$dOCLCO$$dCOM$$dOCLCQ
001434674 049__ $$aISEA
001434674 050_4 $$aTA1634
001434674 08204 $$a006.3/7$$223
001434674 1112_ $$aInternational Conference on Pattern Recognition$$n(25th :$$d2021 :$$cOnline)
001434674 24510 $$aPattern Recognition :$$bICPR International Workshops and Challenges, virtual event, January 10-15, 2021, proceedings.$$nPart VI /$$cAlberto Del Bimbo, Rita Cucchiara, Stan Sclaroff, Giovanni Maria Farinella, Tao Mei, Marco Bertini, Hugo Jair Escalante, Roberto Vezzani (eds.).
001434674 2463_ $$aICPR 2020
001434674 2463_ $$aICPR International Workshops and Challenges
001434674 264_1 $$aCham :$$bSpringer,$$c[2021]
001434674 300__ $$a1 online resource (xx, 821 pages) :$$billustrations (some color)
001434674 336__ $$atext$$btxt$$2rdacontent
001434674 337__ $$acomputer$$bc$$2rdamedia
001434674 338__ $$aonline resource$$bcr$$2rdacarrier
001434674 4901_ $$aLecture notes in computer science,$$x0302-9743 ;$$v12666
001434674 4901_ $$aLNCS sublibrary. SL6 - Image processing, computer vision, pattern recognition, and graphics
001434674 500__ $$aInternational conference proceedings.
001434674 500__ $$aIncludes author index.
001434674 50580 $$g[I].$$tMAES -- Machine Learning Advances Environmental Science:$$tFinding Relevant Flood Images on Twitter Using Content-Based Filters /$$rBjörn Barz, Kai Schröter, Ann-Christin Kra, Joachim Denzler --$$tNatural Disaster Classification Using Aerial Photography Explainable for Typhoon Damaged Feature /$$rTakato Yasuno, Masazumi Amakata, Masahiro Okano --$$tEnvironmental Time Series Prediction with Missing Data by Machine Learning and Dynamics Recostruction /$$rFrancesco Camastra, Vincenzo Capone, Angelo Ciaramella, Tony Christian Landi, Angelo Riccio, Antonino Staiano --$$tSemi-Supervised Learning for Grain Size Distribution Interpolation /$$rKonstantin Kobs, Christian Schäfer, Michael Steininger, Anna Krause, Roland Baumhauer, Heiko Paeth et al. --$$tLocation-Specific vs Location-Agnostic Machine Learning Metamodels for Predicting Pasture Nitrogen Response Rate /$$rChristos Pylianidis, Val Snow, Dean Holzworth, Jeremy Bryant, Ioannis N. Athanasiadis --$$tPattern Classification from Multi-beam Acoustic Data Acquired in Kongsfjorden /$$rGiovanni Giacalone, Giosué Lo Bosco, Marco Barra, Angelo Bonanno, Giuseppa Buscaino, Riko Noormets et al. --$$tUnsupervised Classification of Acoustic Echoes from Two Krill Species in the Southern Ocean (Ross Sea) /$$rIgnazio Fontana, Giovanni Giacalone, Riccardo Rizzo, Marco Barra, Olga Mangoni, Angelo Bonanno et al. --$$tMulti-Input ConvLSTM for Flood Extent Prediction /$$rLeo Muckley, James Garforth --$$tDeveloping a Segmentation Model for Microscopic Images of Microplastics Isolated from Clams /$$rJi Yeon Baek, Maria Krishna de Guzman, Ho-min Park, Sanghyeon Park, Boyeon Shin, Tanja Cirkovic Velickovic et al. --$$tA Machine Learning Approach to Chlorophyll a Time Series Analysis in the Mediterranean Sea /$$rF. Mattei, M. Scardi
001434674 50580 $$tPlankton Recognition in Images with Varying Size /$$rJaroslav Bureš, Tuomas Eerola, Lasse Lensu, Heikki Kälviäinen, Pavel Zemčík --$$tEnvironment Object Detection for Marine ARGO Drone by Deep Learning /$$rAngelo Ciaramella, Francesco Perrotta, Gerardo Pappone, Pietro Aucelli, Francesco Peluso, Gaia Mattei --$$tUnsupervised Learning of High Dimensional Environmental Data Using Local Fractality Concept /$$rMikhail Kanevski, Mohamed Laib --$$tSpatiotemporal Air Quality Inference of Low-Cost Sensor Data; Application on a Cycling Monitoring Network /$$rJelle Hofman, Tien Huu Do, Xuening Qin, Esther Rodrigo, Martha E. Nikolaou, Wilfried Philips et al. --$$tHow Do Deep Convolutional SDM Trained on Satellite Images Unravel Vegetation Ecology? /$$rBenjamin Deneu, Alexis Joly, Pierre Bonnet, Maximilien Servajean, François Munoz.
001434674 50580 $$g[II].$$tManifLearn -- Manifold Learning in Machine Learning, from Euclid to Riemann :$$tImproving Neural Network Robustness Through Neighborhood Preserving Layers /$$rBingyuan Liu, Christopher Malon, Lingzhou Xue, Erik Kruus --$$tMetric Learning on the Manifold of Oriented Ellipses: Application to Facial Expression Recognition /$$rMohamed Daoudi, Naima Otberdout, Juan-Carlos Álvarez Paiva.
001434674 50580 $$g[III].$$tMANPU -- The 4th International Workshop on coMics ANalysis, Processing and Understanding:$$tAn OCR Pipeline and Semantic Text Analysis for Comics /$$rRita Hartel, Alexander Dunst --$$tManga Vocabulometer, A New Support System for Extensive Reading with Japanese Manga Translated into English /$$rJin Kato, Motoi Iwata, Koichi Kise --$$tAutomatic Landmark-Guided Face Image Generation for Anime Characters Using C2GAN /$$rJunki Oshiba, Motoi Iwata, Koichi Kise --$$tText Block Segmentation in Comic Speech Bubbles /$$rChristophe Rigaud, Nhu-Van Nguyen, Jean-Christophe Burie.
001434674 50580 $$g[IV].$$tMMDLCA -- Multi-modal Deep Learning: Challenges and Applications:$$tHierarchical Consistency and Refinement for Semi-supervised Medical Segmentation /$$rZixiao Wang, Hai Xu, Youliang Tian, Hongtao Xie --$$tBVTNet: Multi-label Multi-class Fusion of Visible and Thermal Camera for Free Space and Pedestrian Segmentation /$$rVijay John, Ali Boyali, Simon Thompson, Seiichi Mita --$$tMultimodal Emotion Recognition Based on Speech and Physiological Signals Using Deep Neural Networks /$$rAli Bakhshi, Stephan Chalup --$$tCross-modal Deep Learning Applications: Audio-Visual Retrieval /$$rCong Jin, Tian Zhang, Shouxun Liu, Yun Tie, Xin Lv, Jianguang Li et al. --$$tExploiting Word Embeddings for Recognition of Previously Unseen Objects /$$rKaran Sharma, Hemanth Dandu, Arun C.S. Kumar, Vinay Kumar, Suchendra M. Bhandarkar --$$tAutomated Segmentation of Lateral Ventricle in MR Images Using Multi-scale Feature Fusion Convolutional Neural Network /$$rFei Ye, Zhiqiang Wang, Kai Hu, Sheng Zhu, Xieping Gao --$$tVisual Word Embedding for Text Classification /$$rIgnazio Gallo, Shah Nawaz, Nicola Landro, Riccardo La Grassainst --$$tCC-LSTM: Cross and Conditional Long-Short Time Memory for Video Captioning /$$rJiangbo Ai, Yang Yang, Xing Xu, Jie Zhou, Heng Tao Shen --$$tAn Overview of Image-to-Image Translation Using Generative Adversarial Networks /$$rXin Chen, Caiyan Jia --$$tFusion Models for Improved Image Captioning /$$rMarimuthu Kalimuthu, Aditya Mogadala, Marius Mosbach, Dietrich Klakow --$$tFrom Bottom to Top: A Coordinated Feature Representation Method for Speech Recognition /$$rLixia Zhou, Jun Zhang.
001434674 50580 $$g[V].$$tMMForWild2020 -- MultiMedia FORensics in the WILD 2020:$$tIncreased-Confidence Adversarial Examples for Deep Learning Counter-Forensics /$$rWenjie Li, Benedetta Tondi, Rongrong Ni, Mauro Barni --$$tDefending Neural ODE Image Classifiers from Adversarial Attacks with Tolerance Randomization /$$rFabio Carrara, Roberto Caldelli, Fabrizio Falchi, Giuseppe Amato --$$tAnalysis of the Scalability of a Deep-Learning Network for Steganography "Into the Wild" /$$rHugo Ruiz, Marc Chaumont, Mehdi Yedroudj, Ahmed Oulad Amara, Frédéric Comby, Gérard Subsol --$$tForensics Through Stega Glasses: The Case of Adversarial Images /$$rBenoît Bonnet, Teddy Furon, Patrick Bas --$$tLSSD: A Controlled Large JPEG Image Database for Deep-Learning-Based Steganalysis "Into the Wild" /$$rHugo Ruiz, Mehdi Yedroudj, Marc Chaumont, Frédéric Comby, Gérard Subsol --$$tNeural Network for Denoising and Reading Degraded License Plates /$$rGianmaria Rossi, Marco Fontani, Simone Milani --$$tThe Forchheim Image Database for Camera Identification in the Wild /$$rBenjamin Hadwiger, Christian Riess --$$tNested Attention U-Net: A Splicing Detection Method for Satellite Images /$$rJános Horváth, Daniel Mas Montserrat, Edward J. Delp, János Horváth --$$tFingerprint Adversarial Presentation Attack in the Physical Domain /$$rStefano Marrone, Roberto Casula, Giulia Orrù, Gian Luca Marcialis, Carlo Sansone --$$tLearning to Decipher License Plates in Severely Degraded Images /$$rPaula Kaiser, Franziska Schirrmacher, Benedikt Lorch, Christian Riess --$$tDifferential Morphed Face Detection Using Deep Siamese Networks /$$rSobhan Soleymani, Baaria Chaudhary, Ali Dabouei, Jeremy Dawson, Nasser M. Nasrabadi --$$tIn-Depth DCT Coefficient Distribution Analysis for First Quantization Estimation /$$rSebastiano Battiato, Oliver Giudice, Francesco Guarnera, Giovanni Puglisi.
001434674 50580 $$g[VI].$$tMOI2QDN -- Workshop on Metrification and Optimization of Input Image Quality in Deep Networks:$$tOn the Impact of Rain over Semantic Segmentation of Street Scenes /$$rSimone Zini, Marco Buzzelli --$$tThe Impact of Linear Motion Blur on the Object Recognition Efficiency of Deep Convolutional Neural Networks /$$rJosé A. Rodríguez-Rodríguez, Miguel A. Molina-Cabello, Rafaela Benítez-Rochel, Ezequiel López-Rubio --$$tPerformance of Deep Learning and Traditional Techniques in Single Image Super-Resolution of Noisy Images /$$rKarl Thurnhofer-Hemsi, Guillermo Ruiz-Álvarez, Rafael Marcos Luque-Baena, Miguel A. Molina-Cabello, Ezequiel López-Rubio --$$tThe Effect of Noise and Brightness on Convolutional Deep Neural Networks /$$rJosé A. Rodríguez-Rodríguez, Miguel A. Molina-Cabello, Rafaela Benítez-Rochel, Ezequiel López-Rubio --$$tExploring the Contributions of Low-Light Image Enhancement to Network-Based Object Detection/$$rYuen Peng Loh --$$tMulti-level Fusion Based Deep Convolutional Network for Image Quality Assessment /$$rQianyu Gui, Jing Wen --$$tCNN Based Predictor of Face Image Quality /$$rAndrii Yermakov, Vojtech Franc.
001434674 50580 $$g[VII].$$tMPRSS -- 6th IAPR Workshop on Multimodal Pattern Recognition for Social Signal Processing in Human Computer Interaction:$$tExplainable Model Selection of a Convolutional Neural Network for Driver's Facial Emotion Identification /$$rAmany A. Kandeel, Hazem M. Abbas, Hossam S. Hassanein --$$tArtificial Kindness The Italian Case of Google Mini Recognition Patterns/$$rConcetta Papapicco --$$tFingerspelling Recognition with Two-Steps Cascade Process of Spotting and Classification /$$rMasanori Muroi, Naoya Sogi, Nobuko Kato, Kazuhiro Fukui --$$tCNN Depression Severity Level Estimation from Upper Body vs. Face-Only Images /$$rDua'a Ahmad, Roland Goecke, James Ireland --$$tRange-Doppler Hand Gesture Recognition Using Deep Residual-3DCNN with Transformer Network /$$rGaurav Jaswal, Seshan Srirangarajan, Sumantra Dutta Roy --$$tIntroducing Bidirectional Ordinal Classifier Cascades Based on a Pain Intensity Recognition Scenario /$$rPeter Bellmann, Ludwig Lausser, Hans A. Kestler, Friedhelm Schwenker --$$tPersonalized k-fold Cross-Validation Analysis with Transfer from Phasic to Tonic Pain Recognition on X-ITE Pain Database /$$rYoussef Wally, Yara Samaha, Ziad Yasser, Steffen Walter, Friedhelm Schwenker --$$tODANet: Online Deep Appearance Network for Identity-Consistent Multi-person Tracking /$$rGuillaume Delorme, Yutong Ban, Guillaume Sarrazin, Xavier Alameda-Pineda.
001434674 506__ $$aAccess limited to authorized users.
001434674 520__ $$aThis 8-volumes set constitutes the refereed of the 25th International Conference on Pattern Recognition Workshops, ICPR 2020, held virtually in Milan, Italy and rescheduled to January 10 - 11, 2021 due to Covid-19 pandemic. The 416 full papers presented in these 8 volumes were carefully reviewed and selected from about 700 submissions. The 46 workshops cover a wide range of areas including machine learning, pattern analysis, healthcare, human behavior, environment, surveillance, forensics and biometrics, robotics and egovision, cultural heritage and document analysis, retrieval, and women at ICPR2020.
001434674 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed March 25, 2021).
001434674 650_0 $$aComputer vision$$vCongresses.
001434674 650_0 $$aPattern recognition systems$$vCongresses.
001434674 650_0 $$aPattern perception$$vCongresses.
001434674 650_0 $$aArtificial intelligence$$vCongresses.
001434674 650_0 $$aOptical data processing.
001434674 650_0 $$aApplication software.
001434674 650_0 $$aArtificial intelligence.
001434674 650_0 $$aComputers.
001434674 650_6 $$aVision par ordinateur$$vCongrès.
001434674 650_6 $$aReconnaissance des formes (Informatique)$$vCongrès.
001434674 650_6 $$aPerception des structures$$vCongrès.
001434674 650_6 $$aIntelligence artificielle$$vCongrès.
001434674 650_6 $$aTraitement optique de l'information.
001434674 650_6 $$aLogiciels d'application.
001434674 650_6 $$aIntelligence artificielle.
001434674 650_6 $$aOrdinateurs.
001434674 655_7 $$aConference papers and proceedings.$$2fast$$0(OCoLC)fst01423772
001434674 655_7 $$aConference papers and proceedings.$$2lcgft
001434674 655_7 $$aActes de congrès.$$2rvmgf
001434674 655_0 $$aElectronic books.
001434674 7001_ $$aDel Bimbo, Alberto,$$eeditor.
001434674 7001_ $$aCucchiara, Rita,$$eeditor.
001434674 7001_ $$aSclaroff, Stan,$$eeditor.
001434674 7001_ $$aFarinella, Giovanni Maria,$$eeditor.
001434674 7001_ $$aMei, Tao,$$eeditor.
001434674 7001_ $$aBertini, Marco,$$eeditor.
001434674 7001_ $$aEscalante, Hugo Jair,$$eeditor.
001434674 7001_ $$aVezzani, Roberto,$$eeditor.
001434674 77608 $$iPrint version:$$z9783030687793
001434674 77608 $$iPrint version:$$z9783030687816
001434674 830_0 $$aLecture notes in computer science ;$$v12666.$$x0302-9743
001434674 830_0 $$aLNCS sublibrary.$$nSL 6,$$pImage processing, computer vision, pattern recognition, and graphics.
001434674 852__ $$bebk
001434674 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-68780-9$$zOnline Access$$91397441.1
001434674 909CO $$ooai:library.usi.edu:1434674$$pGLOBAL_SET
001434674 980__ $$aBIB
001434674 980__ $$aEBOOK
001434674 982__ $$aEbook
001434674 983__ $$aOnline
001434674 994__ $$a92$$bISE