A survey of ensemble learning: Concepts, algorithms, applications, and prospects

ID Mienye, Y Sun - Ieee Access, 2022 - ieeexplore.ieee.org
Ensemble learning techniques have achieved state-of-the-art performance in diverse
machine learning applications by combining the predictions from two or more base models …

Deepfake audio detection via MFCC features using machine learning

A Hamza, ARR Javed, F Iqbal, N Kryvinska… - IEEE …, 2022 - ieeexplore.ieee.org
Deepfake content is created or altered synthetically using artificial intelligence (AI)
approaches to appear real. It can include synthesizing audio, video, images, and text …

A novel plagiarism detection approach combining bert-based word embedding, attention-based lstms and an improved differential evolution algorithm

SV Moravvej, SJ Mousavirad, D Oliva… - arxiv preprint arxiv …, 2023 - arxiv.org
Detecting plagiarism involves finding similar items in two different sources. In this article, we
propose a novel method for detecting plagiarism that is based on attention mechanism …

Prediction and explanation of debris flow velocity based on multi-strategy fusion Stacking ensemble learning model

T Wang, K Zhang, Z Liu, T Ma, R Luo, H Chen… - Journal of …, 2024 - Elsevier
The debris flow velocity fundamentally determines its intensity, thereby rendering its
prediction a crucial aspect of disaster prevention and control strategies. However, accurate …

LSTM‐DGWO‐Based Sentiment Analysis Framework for Analyzing Online Customer Reviews

K Barik, S Misra, AK Ray… - Computational Intelligence …, 2023 - Wiley Online Library
Sentiment analysis furnishes consumer concerns regarding products, enabling product
enhancement development. Existing sentiment analysis using machine learning techniques …

[HTML][HTML] Understanding writing style in social media with a supervised contrastively pre-trained transformer

J Huertas-Tato, A Martín, D Camacho - Knowledge-Based Systems, 2024 - Elsevier
Abstract We introduce the Style Transformer for Authorship Representations (STAR) to
detect and characterize writing style in social media. The model is trained on a …

[HTML][HTML] An ensemble learning model for predicting the intention to quit among employees using classification algorithms

AK Biswas, R Seethalakshmi, P Mariappan… - Decision Analytics …, 2023 - Elsevier
Employees are often more likely to use social media for job searching, which sometimes
causes withdrawal behaviour. This study proposes an ensemble learning model for …

An efficient approach for textual data classification using deep learning

A Alqahtani, H Ullah Khan, S Alsubai, M Sha… - Frontiers in …, 2022 - frontiersin.org
Text categorization is an effective activity that can be accomplished using a variety of
classification algorithms. In machine learning, the classifier is built by learning the features of …

HANSEN: human and AI spoken text benchmark for authorship analysis

NI Tripto, A Uchendu, T Le, M Setzu, F Giannotti… - arxiv preprint arxiv …, 2023 - arxiv.org
Authorship Analysis, also known as stylometry, has been an essential aspect of Natural
Language Processing (NLP) for a long time. Likewise, the recent advancement of Large …

Super-resolution multimode fiber imaging with an untrained neural network

W Li, K Abrashitova, LV Amitonova - Optics Letters, 2023 - opg.optica.org
Multimode fiber endoscopes provide extreme miniaturization of imaging components for
minimally invasive deep tissue imaging. Typically, such fiber systems suffer from low spatial …