Pattern Recognition

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 15, 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.

Inhalt

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.