| |
|
|
|
|
|
|
|
|
1. |
Record Nr. |
UNICAMPANIASUN0039693 |
|
|
Autore |
British Museum. Department of Prints and Drawings |
|
|
Titolo |
Italian drawings in the Department of prints and drawings in the British Museum |
|
|
|
|
|
|
|
Pubbl/distr/stampa |
|
|
London : published for the Trustees of the British Museum by British Museum |
|
|
|
|
|
|
|
|
|
Descrizione fisica |
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
Formato |
Materiale a stampa |
|
|
|
|
|
Livello bibliografico |
Monografia |
|
|
|
|
|
2. |
Record Nr. |
UNINA9910983348703321 |
|
|
Autore |
Hernández-García Ruber |
|
|
Titolo |
Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications : 27th Iberoamerican Congress, CIARP 2024, Talca, Chile, November 26–29, 2024, Proceedings, Part I / / edited by Ruber Hernández-García, Ricardo J. Barrientos, Sergio A. Velastin |
|
|
|
|
|
|
|
Pubbl/distr/stampa |
|
|
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
|
|
|
|
|
|
|
ISBN |
|
9783031766077 |
9783031766060 |
|
|
|
|
|
|
|
|
Edizione |
[1st ed. 2025.] |
|
|
|
|
|
Descrizione fisica |
|
1 online resource (0 pages) |
|
|
|
|
|
|
Collana |
|
Lecture Notes in Computer Science, , 1611-3349 ; ; 15368 |
|
|
|
|
|
|
Altri autori (Persone) |
|
BarrientosRicardo J |
VelastinSergio A |
|
|
|
|
|
|
|
|
Disciplina |
|
|
|
|
|
|
Soggetti |
|
Pattern recognition systems |
Machine learning |
Computer vision |
Computer engineering |
Computer networks |
Automated Pattern Recognition |
Machine Learning |
Computer Vision |
Computer Engineering and Networks |
|
|
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
|
|
|
|
|
|
Formato |
Materiale a stampa |
|
|
|
|
|
Livello bibliografico |
Monografia |
|
|
|
|
|
Nota di contenuto |
|
Towards a lightweight CNN for semantic food segmentation -- Ensemble approach to adaptable behavior cloning for a fighting game AI -- TeleoWatch PoseTransformer Based Advanced Action Recognition -- Fruit Deformity Classification through Single Input and Multi Input Architectures based on CNN Models using Real and Synthetic Images -- CNN sensitivity analysis for land cover map models using sparse and heterogeneous satellite data -- Video Game Joystick by Recognizing Breathing Patterns -- Recovering Latent Hierarchical Relationships in Image Datasets Through Hyperbolic Embeddings -- SwinDehazing Haze Removal using U Net and Swin Transformer -- A proposal for explainable fruit quality recognition using multimodal models -- Negative Sampling for Triplet Based Loss Improving Representation in Self Supervised Representation Learning -- Seed based superpixel re segmentation for improving object delineation -- Towards Interactive Video Segmentation by Dynamic and Iterative Spanning Forest -- Data Driven Evolutionary Algorithms for Optimizing Pumping Stations in Water Distribution Networks Classifier Guided Search Space Reduction -- Depth Map Completion using a Specific Graph Metric and Balanced Infinity Laplacian for Autonomous Vehicles -- Beta distribution approach for outlier exposure in multi class text classification -- Impact of Quantization on Large Language Models for Portuguese Classification Tasks -- GemBode and PhiBode Adapting Small Language Models to Brazilian Portuguese -- Hate Speech Detection in Portuguese Using BERTimbau -- An Effective Approach to Text Detection and Recognition in Degraded Historical Documents. |
|
|
|
|
|
|
|
|
Sommario/riassunto |
|
This two-volume set LNCS 15368-15369 constitutes the refereed proceedings of the 27th Iberoamerican Congress on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, CIARP 2024, held in Talca, Chile, during November 26-29, 2024. The 35 full and 3 short papers presented in these proceedings were carefully reviewed and selected from 61 submissions. The papers presented in these two volumes are clustered into various thematical issues as follows: Part I: Mathematical methods and computing techniques for artificial intelligence and pattern recognition, bioinformatics. Part II: Biometrics, cognitive and humanoid vision, computer vision, image analysis, intelligent data analysis. |
|
|
|
|
|
|
|
| |