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Recognizing online video genres using ensemble deep convolutional learning for digital media service management
It's evident that streaming services increasingly seek to automate the generation of film genres, a factor profoundly sha** a film's structure and...
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A study of machine learning-based models for detection, control, and mitigation of cyberbullying in online social media
Online social media (OSM) is an integral part of human life these days. Significantly, the young generation spends most of their time on social media...
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Facial expression recognition of online learners from real-time videos using a novel deep learning model
In every learning setting, in classrooms or online, a student's emotions throughout course involvement play a critical role. It employs disturbing,...
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OEC: an online ensemble classifier for mining data streams with noisy labels
Distilling actionable patterns from large-scale streaming data in the presence of concept drift is a challenging problem, especially when data is...
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Analyzing online public opinion on Thailand-China high-speed train and Laos-China railway mega-projects using advanced machine learning for sentiment analysis
Sentiment analysis is becoming a very popular research technique. It can effectively identify hidden emotional trends in social networks to...
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High-Probability Kernel Alignment Regret Bounds for Online Kernel Selection
In this paper, we study data-dependent regret bounds for online kernel selection in the regime online classification with the hinge loss. Existing...
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Robust semi-supervised discriminant embedding method with soft label in kernel space
Considering some problems of local linear embedding methods in semi-supervised scenarios, a robust scheme for generating soft labels is designed and...
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ABOT: an open-source online benchmarking tool for machine learning-based artefact detection and removal methods from neuronal signals
Brain signals are recorded using different techniques to aid an accurate understanding of brain function and to treat its disorders. Untargeted...
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Incremental and sequence learning algorithms for weighted regularized extreme learning machines
The adoption of weighted regularized extreme learning machines (WR-ELMs) has been recognized as an effective approach to addressing class imbalance...
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ExpertosLF: dynamic late fusion of CBIR systems using online learning with relevance feedback
One of the main challenges in CBIR systems is to choose discriminative and compact features, among dozens, to represent the images under comparison....
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Application of Deep Kernel Models for Certified and Adaptive RB-ML-ROM Surrogate Modeling
In the framework of reduced basis methods, we recently introduced a new certified hierarchical and adaptive surrogate model, which can be used for...
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Blind Image Deblurring with Unknown Kernel Size and Substantial Noise
Blind image deblurring (BID) has been extensively studied in computer vision and adjacent fields. Modern methods for BID can be grouped into two...
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Minimum variance embedded auto-associative kernel extreme learning machine for one-class classification
One-class classification (OCC) needs samples from only a single class to train the classifier. Recently, an auto-associative kernel extreme learning...
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CKR-Calibrator: Convolution Kernel Robustness Evaluation and Calibration
Recently, Convolution Neural Networks (CNN) have achieved excellent performance in some areas of computer vision, including face recognition,...
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Twitter sentiment analysis on online food services based on elephant herd optimization with hybrid deep learning technique
Twitter is a social media stage, making it a valuable resource for learning about people’s opinions, feelings, and thoughts. For this reason, experts...
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Density kernel depth for outlier detection in functional data
In this paper, we propose a novel approach to address the problem of functional outlier detection. Our method leverages a low-dimensional and stable...
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Video based action detection for online exam proctoring in resource-constrained settings
Academic misconduct is a growing problem in online education. While there are ways to curb academic misconduct in online exams, utilization of...
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Large-Kernel Attention for 3D Medical Image Segmentation
Automated segmentation of multiple organs and tumors from 3D medical images such as magnetic resonance imaging (MRI) and computed tomography (CT)...
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A practical approach to learning Linux vulnerabilities
Operating systems based on the Linux kernel are widespread in the microcomputer, mobile, server, and supercomputer market. They have become an...
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Data stream classification using a deep transfer learning method based on extreme learning machine and recurrent neural network
Deep learning-based approaches have gained popularity for many applications in recent years and have become the state-of-the-art method in machine...
