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Multi-class classification of breast cancer abnormality using transfer learning
According to the survey of World Health Organization (WHO), in 2020 there are 2.3 million women found with breast cancer and 685,000 deaths in world...
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Detection of driver drowsiness using transfer learning techniques
Major traffic accidents are often caused by driver drowsiness. Modern lifestyles reduce the amount of sleep an individual gets. Hence, this paper...
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Few-shot transfer learning for wearable IMU-based human activity recognition
Deep learning has proven to be highly effective for human activity recognition (HAR) when large amount of labelled data is available for the target...
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Efficient plant disease identification using few-shot learning: a transfer learning approach
Traditional disease identification methods are time-consuming and necessitate specialized knowledge, making them unsuitable for large-scale crop...
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Automatic glaucoma detection from fundus images using transfer learning
Glaucoma is an eye disease that damages the optic nerve (or retina) and impairs vision. This disease can be prevented with regular checkups, but this...
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Transfer Learning-Hierarchical Segmentation on COVID CT Scans
COVID-19—A pandemic declared by WHO in 2019 has spread worldwide, leading to many infections and deaths. The disease is fatal, and the patient...
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Transfer learning based epileptic seizure classification using scalogram images of EEG signals
Epilepsy is a common neurological disorder that occurs due to an abnormality of the nerve cells in the brain. Electroencephalogram (EEG) analysis is...
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A convergence algorithm for graph co-regularized transfer learning
Transfer learning is an important technology in addressing the problem that labeled data in a target domain are difficult to collect using extensive...
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Understanding transfer learning and gradient-based meta-learning techniques
Deep neural networks can yield good performance on various tasks but often require large amounts of data to train them. Meta-learning received...
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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...
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Word embeddings-based transfer learning for boosted relational dependency networks
Conventional machine learning methods assume data to be independent and identically distributed (i.i.d.) and ignore the relational structure of the...
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Instance-based transfer learning
In this segment, we introduce the instance-based transfer learning approach, which can be categorized as instance selection and instance weighting...
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Safe and Robust Transfer Learning
In this chapter, we discuss the safety and robustness of transfer learning. By safety, we refer to its defense and solutions against attack and data...
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Federated transfer learning for intrusion detection system in industrial iot 4.0
A major concern for Industry 4.0 is security issues because of several new cyber-security risks. In recent eras, various Deep Learning methods have...
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Video-based beat-by-beat blood pressure monitoring via transfer deep-learning
AbstractCurrently, learning physiological vital signs such as blood pressure (BP), hemoglobin levels, and oxygen saturation, from...
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GeoTrans: a transfer learning approach for estimating petrophysical properties from geophysical sensors data
Petrophysical properties estimation is vital in reservoir characterisation domain to identify the prospect locations of presence of petroleum....
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Identification of apple leaf diseases using C-Grabcut algorithm and improved transfer learning base on low shot learning
Plant disease control is an indispensable research topic in the field of agriculture. Different apple leaf diseases may have similar manifestations,...
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Feature-based transfer learning
In this segment, feature-based transfer learning approaches are introduced. Specifically, we introduce two main categories: explict distance and...
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Quantifying image naturalness using transfer learning and fusion model
Distinguishing a natural scene from artwork is a simple task for the human visual system, but a challenging one for machines due to the wide range of...
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Multilingual, monolingual and mono-dialectal transfer learning for Moroccan Arabic sentiment classification
Transfer learning has recently proven to be very powerful in diverse natural language processing (NLP) tasks such as Machine translation, Sentiment...