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Transfer learning-based quantized deep learning models for nail melanoma classification
Skin cancer, particularly melanoma, has remained a severe issue for many years due to its increasing incidences. The rising mortality rate associated...
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Facial Expression Recognition Using Machine Learning and Deep Learning Techniques: A Systematic Review
In the contemporary era, Facial Expression Recognition (FER) plays a pivotal role in numerous fields due to its vast application areas, such as...
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Learning elements for develo** higher-order thinking in a blended learning environment: A comprehensive survey of Chinese vocational high school students
The significance of higher-order thinking (HOT) is becoming increasingly prominent in the twenty-first century, as reflected in the framework of most...
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Addressing the data bottleneck in medical deep learning models using a human-in-the-loop machine learning approach
Any machine learning (ML) model is highly dependent on the data it uses for learning, and this is even more important in the case of deep learning...
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Performance evaluation of Dictionary Learning and ICA on Parkinson’s patients classification using Machine Learning
Currently, extensive research is being conducted in the application of Machine Learning (ML) algorithms in the medical domain and one such area is...
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Transfer learning based cascaded deep learning network and mask recognition for COVID-19
The COVID-19 is still spreading today, and it has caused great harm to human beings. The system at the entrance of public places such as shop**...
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A Deep Learning Based Approach for Biomedical Named Entity Recognition Using Multitasking Transfer Learning with BiLSTM, BERT and CRF
The named entity recognition (NER) is a method for locating references to rigid designators in text that fall into well-established semantic...
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TransNet: a comparative study on breast carcinoma diagnosis with classical machine learning and transfer learning paradigm
Breast Carcinoma is a deadly disease; therefore, timely diagnosis is one of the most critical concerns that must be addressed globally since it can...
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Anthropomorphised learning contents: Investigating learning outcomes, epistemic emotions and gaze behaviour
Anthropomorphism is defined as attributing human traits and emotions to non-human entities. In the field of emotional design in multimedia learning,...
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Machine learning and deep learning models for human activity recognition in security and surveillance: a review
Human activity recognition (HAR) has received the significant attention in the field of security and surveillance due to its high potential for...
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Control learning rate for autism facial detection via deep transfer learning
Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder that affects social interaction and communication. Early detection of ASD can...
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COVID-19 classification based on a deep learning and machine learning fusion technique using chest CT images
Coronavirus disease (COVID-19), impacted by SARS-CoV-2, is one of the greatest challenges of the twenty-first century. COVID-19 broke out in the...
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A comparative analysis of classical machine learning and deep learning techniques for predicting lung cancer survivability
Lung cancer, one of the deadliest forms of cancer, can significantly improve patient survival rates by 60–70% if detected in its early stages. The...
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Deep learning approaches for lyme disease detection: leveraging progressive resizing and self-supervised learning models
Lyme disease diagnosis poses a significant challenge, with blood tests exhibiting an alarming inaccuracy rate of nearly 60% in detecting early-stage...
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Universal representation learning for multivariate time series using the instance-level and cluster-level supervised contrastive learning
The multivariate time series classification (MTSC) task aims to predict a class label for a given time series. Recently, modern deep learning-based...
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Hyperspectral image classification via active learning and broad learning system
Hyperspectral image (HSI) classification has continued to be a hot research topic in recent years, and the broad learning system (BLS) has been...
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A two-phase projective dictionary pair learning-based classification scheme for positive and unlabeled learning
With the recent surge of interest in machine learning, Positive and Unlabeled learning (PU learning) has also attracted much attention of scholars. A...
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Semantic speech analysis using machine learning and deep learning techniques: a comprehensive review
Human cognitive functions such as perception, attention, learning, memory, reasoning, and problem-solving are all significantly influenced by...
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Communication-efficient federated continual learning for distributed learning system with Non-IID data
Due to the privacy preserving capabilities and the low communication costs, federated learning has emerged as an efficient technique for distributed...
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Leveraging deep learning-assisted attacks against image obfuscation via federated learning
Obfuscation techniques (e.g., blurring) are employed to protect sensitive information (SI) in images such as individuals’ faces. Recent works...
