Fr. 103.00

Pattern Recognition - 27th International Conference, ICPR 2024, Kolkata, India, December 1-5, 2024, Proceedings, Part III

Inglese · Tascabile

Spedizione di solito entro 6 a 7 settimane

Descrizione

Ulteriori informazioni

The multi-volume set of LNCS books with volume numbers 15301-15333 constitutes the refereed proceedings of the 27th International Conference on Pattern Recognition, ICPR 2024, held in Kolkata, India, during December 1-5, 2024.
The 963 papers presented in these proceedings were carefully reviewed and selected from a total of 2106 submissions. They deal with topics such as Pattern Recognition; Artificial Intelligence; Machine Learning; Computer Vision; Robot Vision; Machine Vision; Image Processing; Speech Processing; Signal Processing; Video Processing; Biometrics; Human-Computer Interaction (HCI); Document Analysis; Document Recognition; Biomedical Imaging; Bioinformatics.

Sommario

Deep Multi-order Context-aware Kernel Network for Multi-label Classification.- Classifier Enhanced Deep Learning Model for Erythroblast Differentiation with Limited Data.- PiExtract: An End-to-End Data Extraction pipeline for Pie-Charts.- Machine Learning Solutions for Predicting Bankruptcy  in Indian Firms.- Efficient Object Detection via Fine-grained Regularization with Global Initialization.- On Trace of PGD-Like Adversarial Attacks.- CAB-KWS: Contrastive Augmentation: An Unsupervised Learning Approach for Keyword Spotting in Speech Technology.- Deep Learning in Automated Worm Identification and Tracking for C. Elegan Mating Behaviour Analysis.- Interactive-Time Text-Guided Editing of 3D Face.- Unlearning Vision Transformers without Retaining Data via Low-Rank Decompositions.- gWaveNet: Classification of Gravity Waves from Noisy Satellite Data using Custom Kernel Integrated Deep Learning Method.- Neural-Code PIFu: High-Fidelity Single Image 3D Human Reconstruction via Neural Code Integration.- Sea-ShipNet: Detect Any Ship in SAR Images.- Semantic Correlation Adaptation for Union-Set Multi-Label Image Recognition.- FedSC: Federated Generalized Face Anti-Spoofing via Shuffled Codebook.- LoHoSC: Low Order High Order Style Consistency for Syn-to-Real Domain Generalized Semantic Segmentation.- Incorporating Spatial Locality into Self-Attention for Training Vision Transformer on Small-Scale Datasets.- Cross-Domain Calibration and Boundary Denoising Network for Weakly Supervised Semantic Segmentation.- EFLLD-NET: Enhancing Few-Shot Learning With Local Descriptors.- Using Multiscale Information for Improved Optimization-based Image Attribution.- Split-DNN Computing for Video Analytics.- Task-Aware Local Descriptors Reconstruction Network for Few-Shot Find-Grained Image Classification.- TRIGS: Trojan Identification from Gradient-based Signatures.- Multifaceted Anchor Nodes Attack on Graph Neural Networks: A Budget-efficient Approach.- Causal Attentive Group Recommendation.- E2DAS: An Efficient Equivariant Dynamic Aggregation Saliency Model for Omnidirectional Images.- FewConv: Efficient variant convolution for few-shot image generation.- FixPix: Fixing Bad Pixels using Deep Learning.- Real-world Coarse to Fine-Grained Source-Free Multidomain Adaptation.

Dettagli sul prodotto

Con la collaborazione di Apostolos Antonacopoulos (Editore), Saumik Bhattacharya (Editore), Subhasis Chaudhuri (Editore), Rama Chellappa (Editore), Rama Chellappa et al (Editore), Cheng-Lin Liu (Editore), Umapada Pal (Editore)
Editore Springer, Berlin
 
Titolo originale Pattern Recognition
Lingue Inglese
Formato Tascabile
Pubblicazione 28.12.2024
 
EAN 9783031781216
ISBN 978-3-0-3178121-6
Pagine 474
Dimensioni 155 mm x 27 mm x 235 mm
Peso 768 g
Illustrazioni XXXVII, 474 p. 142 illus., 136 illus. in color.
Serie Lecture Notes in Computer Science
Categorie Scienze naturali, medicina, informatica, tecnica > Informatica, EDP > Software applicativo

machine learning, Maschinelles Lernen, Artificial Intelligence, bioinformatics, Computer Vision, pattern recognition, Signal Processing, Image processing, Biometrics, Biomedical Imaging, speech processing, video processing, Machine Vision, human-computer interaction (HCI), robot vision, Document Recognition, Document Analysis

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