Structural, Syntactic, and Statistical Pattern Recognition Joint IAPR International Workshops, S+SSPR 2024, Venice, Italy, September 9–10, 2024, Revised Selected Papers /

This book constitutes the proceedings of the Joint IAPR International Workshops on Structural, Syntactic, and Statistical Pattern Recognition, S+SSPR 2024, which took place in Venice, Italy, during September 9-11, 2024. The 19 full papers presented in this volume were carefully reviewed and selected...

Täydet tiedot

Tallennettuna:
Bibliografiset tiedot
Yhteisötekijä: SpringerLink (Online service)
Muut tekijät: Torsello, Andrea (Toimittaja), Rossi, Luca (Toimittaja), Cosmo, Luca (Toimittaja), Minello, Giorgia (Toimittaja)
Aineistotyyppi: Elektroninen E-kirja
Kieli:englanti
Julkaistu: Cham : Springer Nature Switzerland : Imprint: Springer, 2025.
Painos:1st ed. 2025.
Sarja:Lecture Notes in Computer Science, 15444
Aiheet:
Linkit:https://doi.org/10.1007/978-3-031-80507-3
Tagit: Lisää tagi
Ei tageja, Lisää ensimmäinen tagi!

MARC

LEADER 00000nam a22000005i 4500
001 978-3-031-80507-3
003 DE-He213
005 20260706115716.0
007 cr nn 008mamaa
008 250131s2025 sz | s |||| 0|eng d
020 |a 9783031805073  |9 978-3-031-80507-3 
024 7 |a 10.1007/978-3-031-80507-3  |2 doi 
050 4 |a Q334-342 
050 4 |a TA347.A78 
072 7 |a UYQ  |2 bicssc 
072 7 |a COM004000  |2 bisacsh 
072 7 |a UYQ  |2 thema 
082 0 4 |a 006.3  |2 23 
245 1 0 |a Structural, Syntactic, and Statistical Pattern Recognition  |h [electronic resource] :  |b Joint IAPR International Workshops, S+SSPR 2024, Venice, Italy, September 9–10, 2024, Revised Selected Papers /  |c edited by Andrea Torsello, Luca Rossi, Luca Cosmo, Giorgia Minello. 
250 |a 1st ed. 2025. 
264 1 |a Cham :  |b Springer Nature Switzerland :  |b Imprint: Springer,  |c 2025. 
300 |a XII, 200 p. 58 illus., 53 illus. in color.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
490 1 |a Lecture Notes in Computer Science,  |x 1611-3349 ;  |v 15444 
505 0 |a  -- A Differentiable Approximation of the Graph Edit Distance. -- Learning Graph Similarity by Counting Holes in Simplicial Complexes. -- Community-Hop: Enhancing Node Classification through Community Preference. -- Spatio-Temporal Graph Neural Networks for Water Temperature Modeling. -- Enhancing IoT Network Security with Graph Neural Networks for Node Anomaly Detection. -- LSTM Networks and Graph Neural Networks for Predicting Events of Hypoglycemia. -- Evaluation metrics in Saliency Maps applied to Graph Regression. -- LESI-GNN: an Interpretable Graph Neural Network based on Local Structures Embedding. -- Mixture of Variational Graph Autoencoders. -- Multimodality Calibration in 3D Multi Input-Multi Output Network for Dementia Diagnosis with Incomplete Acquisitions. -- Multi-modal Medical Images Classification Using Meta-learning Algorithms. -- From semantic segmentation of natural images to medical image segmentation using ViT-based architectures. -- Chronic Wound Segmentation and Measurement Using Semi-Supervised Hierarchical Convolutional Neural Networks. -- ZIRACLE: Zero-shot composed Image Retrieval with Advanced Component-Level Emphasis. -- Improving Object Detector Performance on Low-Quality Images using Histogram Matching and Model Stacking. -- Comparing Learning Methods to Enhance Decision-Making in Simulated Curling. -- An empirical characterization of the stability of Isolation Forest results. -- Automated Classification of Android Games using Word Embeddings. -- An interesting property of Random Forest distances with respect to the curse of dimensionality. 
520 |a This book constitutes the proceedings of the Joint IAPR International Workshops on Structural, Syntactic, and Statistical Pattern Recognition, S+SSPR 2024, which took place in Venice, Italy, during September 9-11, 2024. The 19 full papers presented in this volume were carefully reviewed and selected from 27 submissions. The proceedings focus on pattern recognition, including classification and clustering, deep learning, structural matching and graph-theoretic methods, and multimedia analysis and understanding. 
650 0 |a Artificial intelligence. 
650 0 |a Computer science  |x Mathematics. 
650 0 |a Discrete mathematics. 
650 0 |a Algorithms. 
650 0 |a Computer graphics. 
650 0 |a Computer vision. 
650 0 |a Pattern recognition systems. 
650 1 4 |a Artificial Intelligence. 
650 2 4 |a Discrete Mathematics in Computer Science. 
650 2 4 |a Design and Analysis of Algorithms. 
650 2 4 |a Computer Graphics. 
650 2 4 |a Computer Vision. 
650 2 4 |a Automated Pattern Recognition. 
700 1 |a Torsello, Andrea.  |e editor.  |0 (orcid)0000-0001-9189-4924  |1 https://orcid.org/0000-0001-9189-4924  |4 edt  |4 http://id.loc.gov/vocabulary/relators/edt 
700 1 |a Rossi, Luca.  |e editor.  |0 (orcid)0000-0002-6116-9761  |1 https://orcid.org/0000-0002-6116-9761  |4 edt  |4 http://id.loc.gov/vocabulary/relators/edt 
700 1 |a Cosmo, Luca.  |e editor.  |0 (orcid)0000-0001-7729-4666  |1 https://orcid.org/0000-0001-7729-4666  |4 edt  |4 http://id.loc.gov/vocabulary/relators/edt 
700 1 |a Minello, Giorgia.  |e editor.  |0 (orcid)0000-0002-0923-7640  |1 https://orcid.org/0000-0002-0923-7640  |4 edt  |4 http://id.loc.gov/vocabulary/relators/edt 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer Nature eBook 
776 0 8 |i Printed edition:  |z 9783031805066 
776 0 8 |i Printed edition:  |z 9783031805080 
830 0 |a Lecture Notes in Computer Science,  |x 1611-3349 ;  |v 15444 
856 4 0 |u https://doi.org/10.1007/978-3-031-80507-3 
912 |a ZDB-2-SCS 
912 |a ZDB-2-SXCS 
912 |a ZDB-2-SXPS 
912 |a ZDB-2-LNC 
912 |a ZDB-2-243 
950 |a Computer Science (SpringerNature-11645) 
950 |a Computer Science (R0) (SpringerNature-43710) 
950 |a Springer Nature Proceedings Computer Science (SpringerNature-85344) 
950 |a Focus Bundle Proceedings in AI Research (SpringerNature-85413)