01013nam0-22002891i-450-9900010162304033213-540-17894-5000101623FED01000101623(Aleph)000101623FED01000101623--------d--------km-y0itay50------baeng<<The >>Physics of Phase SpaceNonlinear Dynamics and Chaos, Geometric Quantization, and Wigner FunctionProceedings of the first International Conference held at the University of Maryland, College Park, Maryland, May 20-23, 1986Edited by Y.S. Kim and W.W. ZacharyBerlin [etc.]Springer-Verlag1987Lecture notes in physics278Meccanica classica531Kim,Y. S.48216Zachary,Woodford W.ITUNINARICAUNIMARCBK99000101623040332124-10514199FI1FI1Physics of Phase Space355387UNINA04863nam 22006975 450 991088109730332120240821130242.09783031666940(electronic bk.)978303166693310.1007/978-3-031-66694-0(MiAaPQ)EBC31608964(Au-PeEL)EBL31608964(CKB)34118599200041(DE-He213)978-3-031-66694-0(EXLCZ)993411859920004120240821d2024 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierDeep Learning Theory and Applications 5th International Conference, DeLTA 2024, Dijon, France, July 10–11, 2024, Proceedings, Part I /edited by Ana Fred, Allel Hadjali, Oleg Gusikhin, Carlo Sansone1st ed. 2024.Cham :Springer Nature Switzerland :Imprint: Springer,2024.1 online resource (382 pages)Communications in Computer and Information Science,1865-0937 ;2171Print version: Fred, Ana Deep Learning Theory and Applications Cham : Springer,c2024 9783031666933 Deep Learning for Wearable Biometrics -- A Deep Learning-Based Plant Disease Detection and Classification for Arabica Coffee Leaves -- CNN-N-BEATS: Novel Hybrid Model for Time-Series Forecasting -- Development and Applications of Gesture-Controlled Drones: Advances in Hand Gesture Recognition for Aerial Navigation -- Towards Natural-Sounding Speech to Text in English -- Scoping Review of Active Learning Strategies and Their Evaluation Environments for Entity Recognition Tasks -- Solar Activity Impact on Firefighter Interventions: Factors Analysis -- Detecting Flow via a Machine Learning Model in a MOOC Context -- Online Job Posting Authenticity Prediction with Machine and Deep Learning: Performance Comparison Between N-Gram and TF-IDF -- Evolving Deep Architectures: A New Blend of CNNs and Transformers Without Pre-Training Dependencies.-Closing the Sim-to-Real Gap: Enhancing Autonomous Precision Landing of UAVs with Detection-Informed Deep Reinforcement Learning -- Mitigating Class Imbalance in Healthcare AI Image Classification: Evaluating the Efficacy of Existing Generative Adversarial Network -- More than Noise: Assessing the Viscosity of Food Products Based on Sound Emission -- Vector Analysis of Deep Neural Network Training Process -- Secure Coalition Formation for Federated Machine Learning -- Action Conditioned Attention Encoder-Decoder and Discriminator for Human Motion Generation -- Citation Polarity Identification in Scientific Research Articles Using Deep Learning Methods -- Exploring Physiology-Based Classification of Flow During Musical Improvisation in Mixed Reality -- Refining Weights for Enhanced Object Similarity in Multi-Perspective 6D of Pose Estimation and 3D Object Detection -- End-to-End Video Surveillance Framework for Anomaly Detection and Person Re-Identification -- Few-Shot Learning with Novelty Detection.The two-volume set CCIS 2171 and 2172 constitutes the refereed best papers from the 5th International Conference on Deep Learning Theory and Applications, DeLTA 2024, which took place in Dijon, France, during July 10-11, 2024. The 44 papers included in these proceedings were carefully reviewed and selected from a total of 70 submissions. They focus on topics such as deep learning and big data analytics; machine-learning and artificial intelligence, etc. .Communications in Computer and Information Science,1865-0937 ;2171Artificial intelligenceMachine learningApplication softwareData miningNatural language processing (Computer science)Artificial IntelligenceMachine LearningComputer and Information Systems ApplicationsData Mining and Knowledge DiscoveryNatural Language Processing (NLP)Artificial intelligence.Machine learning.Application software.Data mining.Natural language processing (Computer science).Artificial Intelligence.Machine Learning.Computer and Information Systems Applications.Data Mining and Knowledge Discovery.Natural Language Processing (NLP).006.3Fred Ana1372767Hadjali Allel1372591Gusikhin Oleg1073423Sansone Carlo1372864MiAaPQMiAaPQMiAaPQ9910881097303321Deep Learning Theory and Applications4207477UNINA02086nam0 2200457 i 450 VAN0012373320240806100814.293N978981104205820191001d2017 |0itac50 baengSG|||| |||||Classical Summability TheoryP.N. NatarajanSingaporeSpringer2017xi, 130 p.24 cmVAN00235467Classical Summability Theory156222840-XXSequences, series, summability [MSC 2020]VANC020786MF40AxxConvergence and divergence of infinite limiting processes [MSC 2020]VANC029225MF40CxxGeneral summability methods [MSC 2020]VANC033920MF40DxxDirect theorems on summability [MSC 2020]VANC033921MF40GxxSpecial methods of summability [MSC 2020]VANC033180MFMatrix theoryKW:KProduct theoremKW:KSchur's theoremKW:KSilverman-Toeplitz theoremKW:KSpecial methods of summabilityKW:KSteinhaus type theoremKW:KSGSingaporeVANL000061NatarajanPinnangudi N.VANV081418721163Springer <editore>VANV108073650Natarajan, Pinnangudi NarayanasubramanianNatarajan, Pinnangudi N.VANV233732Natarajan, P.N.Natarajan, Pinnangudi N.VANV233733Natarajan, P. N.Natarajan, Pinnangudi N.VANV233734ITSOL20241115RICAhttp://doi.org/10.1007/978-981-10-4205-8E-book – Accesso al full-text attraverso riconoscimento IP di Ateneo, proxy e/o ShibbolethBIBLIOTECA DEL DIPARTIMENTO DI MATEMATICA E FISICAIT-CE0120VAN08NVAN00123733BIBLIOTECA DEL DIPARTIMENTO DI MATEMATICA E FISICA08DLOAD e-book 0593 08eMF593 20191001 Classical Summability Theory1562228UNICAMPANIA