Titlebook: Artificial Intelligence and Machine Learning; First International Hai Jin,Yi Pan,Jianfeng Lu Conference proceedings 2024 The Editor(s) (if

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Allison Daniel Anders,George W. Noblitnt problem. In this paper, we propose an audio copy-move forgery detection algorithm based on the fusion of mel frequency cepstrum coefficient and gammatone frequency cepstrum coefficient feature fusion. Firstly, the algorithm extracts the voiced speech segments in the audio using the algorithm of v

TERRA

,Evo-Devo – das Beste aus zwei Welten,nsors or sources based on certain standards so as to achieve the required decisions and estimates, and it includes two types of information, homogeneous information and heterogeneous information. MSIF is also referred as multi-sensor information fusion. Rough set theory (RST) provides an effective m

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Machine Printed Page Number Anomaly Detection Method Based on Multi-scale Self Attention Encoding Dphenomena during the printing process. Effective detection of machine printed page numbers is of great practical significance for improving the efficiency of archive organization work; A machine printed page anomaly detection method based on multi-scale self attention encoding decoding is proposed t

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A Novel MEC Framework for Extractive Summarization Using Semantic Role Graph and Semantic Matching,deal with them anytime and anywhere through different terminal devices. Among which, text information usually costs too much time for length and redundancy. Hence, providing an efficient text summarization approach is quite necessary. However, such approaches usually depend on artificial intelligenc

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,A Review of Solving Non-IID Data in Federated Learning: Current Status and Future Directions, train a global model through coordination by a central server while ensuring the privacy of data on individual edge devices. However, the data on edge devices that participate in FL training are not independently and identically distributed (IID), resulting in challenges related to heterogeneity da

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BERT and LLM-Based Multivariate Hate Speech Detection on Twitter: Comparative Analysis and Superiorsequences it can cause. Previous research has demonstrated the vital role that machine learning and natural language processing models have in identifying inappropriate language. In this study, the aim is to assess the viability of BERT for accurately predicting multivariate classifications related