Pattern Recognition : 27th International Conference, ICPR 2024, Kolkata, India, December 1–5, 2024, Proceedings, Part I / edited by Apostolos Antonacopoulos, Subhasis Chaudhuri, Rama Chellappa, Cheng-Lin Liu, Saumik Bhattacharya, Umapada Pal.

Format:

Book

Author/Creator:

Antonacopoulos, Apostolos.

Contributor:

Chaudhuri, Subhasis.

Chellappa, Rama.

Liu, Cheng-Lin.

Bhattacharya, Saumik.

Pal, Umapada.

Series:

Lecture Notes in Computer Science, 1611-3349 ; 15301

Language:

English

Subjects (All):

Computer vision.

Machine learning.

Computer Vision.

Machine Learning.

Local Subjects:

Computer Vision.

Machine Learning.

Physical Description:

1 online resource (507 pages)

Edition:

1st ed. 2025.

Place of Publication:

Cham : Springer Nature Switzerland : Imprint: Springer, 2025.

Summary:

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.

Contents:

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.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

9783031781070

3031781074

OCLC:

1477225573