UID:
almahu_9949930862402882
Umfang:
XXXVII, 470 p. 152 illus., 136 illus. in color.
,
online resource.
Ausgabe:
1st ed. 2025.
ISBN:
9783031781070
Serie:
Lecture Notes in Computer Science, 15301
Inhalt:
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.
Anmerkung:
Semi-Supervised Variational Adversarial Active Learning via Learning to Rank and Agreement-Based Pseudo Labeling -- Deep Evidential Active Learning with Uncertainty-Aware Determinantal Point Process -- Knowledge Distillation in Deep Networks under a Constrained Query Budget -- Adabot: An Adaptive Trading Bot using an Ensemble of Phase-specific Few-shot Learners to Adapt to the Changing Market Dynamics -- Uncertainty in Ambiguity of Data -- When Uncertainty-based Active Learning May Fail -- Customizable and Programmable Deep Learning -- SegXAL: Explainable Active Learning for semantic segmentation in driving scene scenarios -- AMC-OA: Adaptive Multi-Scale Convolutional Networks with Optimized Attention for Temporal Action Localization -- Comparative Analysis Of Pretrained Models for Text Classification, Generation and Summarization : A Detailed Analysis -- Predicting Judgement Outcomes from Legal Case File Summaries with Explainable Approach -- Multi-view Ensemble Clustering-based Podcast Recommendation in Indian Regional Setting -- Privacy-Preserving Ensemble Learning using Fully Homomorphic Encryption -- Capturing Temporal Components for Time Series Classification -- Hierarchical Transfer Multi-task Learning Approach for Scene Classification -- Deep Prompt Multi-task Network for Abuse Language Detection -- All mistakes are not equal: Comprehensive Hierarchy Aware Multilabel Predictions (CHAMP) -- IDAL: Improved Domain Adaptive Learning for Natural Images Dataset -- Large Multimodal Models Thrive with Little Data for Image Emotion Prediction -- Flatter Minima of Loss Landscapes Correspond with Strong Corruption Robustness -- Restoring Noisy Images using Dual-tail Encoder-Decoder Signal Separation Network -- Utilizing Deep Incomplete Classifiers To Implement Semantic Clustering For Killer Whale Photo Identification Data -- FPMT: Enhanced Semi-Supervised Model for Traffic Incident Detection -- C2F-CHART: A Curriculum Learning Approach to Chart Classification -- Vision DualGNN: Semantic Graph is Not Only You Need -- Enhancing Graph-based Clustering Based on the Regularity Lemma -- IPD: Scalable Clustering with Incremental Prototypes -- Mitigating the Impact of Noisy Edges on Graph-Based Algorithms via Adversarial Robustness Evaluation -- Adaptive Graph-based Manifold Learning for Gene Selection.
In:
Springer Nature eBook
Weitere Ausg.:
Printed edition: ISBN 9783031781063
Weitere Ausg.:
Printed edition: ISBN 9783031781087
Sprache:
Englisch
DOI:
10.1007/978-3-031-78107-0
URL:
https://doi.org/10.1007/978-3-031-78107-0
