Neural Information Processing : 31st International Conference, ICONIP 2024, Auckland, New Zealand, December 2–6, 2024, Proceedings, Part XII / edited by Mufti Mahmud, Maryam Doborjeh, Kevin Wong, Andrew Chi Sing Leung, Zohreh Doborjeh, M. Tanveer.

Format:

Book

Author/Creator:

Mahmud, Mufti.

Contributor:

Doborjeh, Maryam.

Huang, Dejiang.

Leung, Andrew Chi Sing.

Doborjeh, Zohreh.

Tanveer, M.

Series:

Communications in Computer and Information Science, 1865-0937 ; 2293

Language:

English

Subjects (All):

Pattern recognition systems.

Data mining.

Machine learning.

Social sciences--Data processing.

Social sciences.

Automated Pattern Recognition.

Data Mining and Knowledge Discovery.

Machine Learning.

Computer Application in Social and Behavioral Sciences.

Local Subjects:

Automated Pattern Recognition.

Data Mining and Knowledge Discovery.

Machine Learning.

Computer Application in Social and Behavioral Sciences.

Physical Description:

1 online resource (759 pages)

Edition:

1st ed. 2025.

Place of Publication:

Singapore : Springer Nature Singapore : Imprint: Springer, 2025.

Summary:

The sixteen-volume set, CCIS 2282-2297, constitutes the refereed proceedings of the 31st International Conference on Neural Information Processing, ICONIP 2024, held in Auckland, New Zealand, in December 2024. The 472 regular papers presented in this proceedings set were carefully reviewed and selected from 1301 submissions. These papers primarily focus on the following areas: Theory and algorithms; Cognitive neurosciences; Human-centered computing; and Applications.

Contents:

Fine-tuning Fine-tuned Models: Towards a Practical Methodology for Sentiment Analysis with Small In-domain Supervised Dataset

End-to-end Knowledge Graph Construction System Powered by Large Language Models

EPRVR: Efficient Partially Relevant Video Retrieval with Disentangled Video Representation Learning

Graph-Based Data Augmentation and Label Noise Identification for Entity Resolution

Patient Mortality prediction Using Clinical Notes

ScaleDoc: A Two-Stage Approach for Scale-Aware Document Dewarping

CCUH:CLIP-Based Clustering Method for Unsupervised Hashing Multi-Modal Retrieval

A Privacy-Preserving Image Classification Framework with Transformer

Reversible Data Hiding in Dual Encrypted Images with Dual Data Embedding

A Dual-Layer Reversible Data Hiding Scheme Based on Optimal Neighbor Mean Interpolation (ONMI) and Histogram Shifting

Threat Intelligence Entity Recognition Based On Large Language Model With Contrastive Learning

GTSD: Generative Text Steganography Based on Diffusion Model

Enhanced Autoencoder Model for Robust Anomaly Detection in Financial Fraud with Imbalanced Data

Membership Inference Attacks in Text Classification Tasks

PURVEY-CE: A Complex texture adaptive image steganography based on channel attention

Air-Sniffing Analytics Enhancing Wi-Fi Device Identification with Robust and Accurate Techniques

Spikewhisper: Temporal Spike Backdoor Attacks on Federated Neuromorphic Learning over Low-power Devices

Control ControlNet: Multidimensional Backdoor Attack based on ControlNet

CPANet: Convolutional Parameter Adapter Network for Image Copy-Move Forgery Detection and Localization

AO-UAP: An Adaptive Universal Adversarial Perturbation Generation for Speech Recognition Models

A Hilbert-Curve based Encoding scheme for Privacy-preserving Nearest-Neighbor Classification

ZKP-HGNN: A Study on Improving Zero- Knowledge Proof (ZKP) Based on Heterogeneous Graph Neural Networks for Anonymous Digital Identity Sharing in Blockchain

Adversarial Knowledge Extraction via Steering Diffusion Models

Solving the Thinnest Path Problem with Hypergraph Learning

AISSGR: Attack Investigation Based on Self-Supervised Graph Representation Learning

Two-stage optimized adversarial patch for attacking infrared vehicle detectors in the physical world

Deep Learning-Based Detection of Code Execution Vulnerabilities in Binary Programs

Towards Real-Time Audio Deepfake Detection in Resource-Limited Environments

Detecting Audio Deepfakes through Emotional Fingerprinting

Constructing Multi-Detector Decision Forest for Fake Speech Detection

KDAE: Kernel Density Auto-Encoder for Semi-Supervised Anomaly Detection with Limited Labeled Data.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

981-9670-05-5

OCLC:

1525622464