Results 41 to 50 of about 338,614 (301)
Learning From Labeled And Unlabeled Data: An Empirical Study Across Techniques And Domains
, 2011 There has been increased interest in devising learning techniques that combine unlabeled data with labeled data ? i.e. semi-supervised learning. However, to the best of our knowledge, no study has been performed across various techniques and different ...
Chawla, N. V., Karakoulas, Grigoris
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Cardiac Imaging with Electrical Impedance Tomography (EIT) using Multilayer Perceptron Network
Jurnal Elektronika dan TelekomunikasiThis research explores the enhancement of Electrical Impedance Tomography (EIT) for cardiac imaging using Multilayer Perceptron (MLP) networks, focusing on supervised and semi-supervised learning approaches.
Amelia Putri Ristyawardani +6 more
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Full body virtual try‐on with semi‐self‐supervised learning
Electronics Letters, 2021 This paper proposes a full body virtual try‐on which handles both top and bottom garments and generates realistic try‐on images. For the full body virtual try‐on, this paper addresses lack of suitable training data to align and fit top and bottom ...
Hyug‐Jae Lee +5 more
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Towards Realistic Semi-supervised Learning
, 2022 Deep learning is pushing the state-of-the-art in many computer vision applications. However, it relies on large annotated data repositories, and capturing the unconstrained nature of the real-world data is yet to be solved. Semi-supervised learning (SSL) complements the annotated training data with a large corpus of unlabeled data to reduce annotation ...
Rizve, Mamshad Nayeem +2 more
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AIFor automatic tumor segmentation in magnetic resonance imaging (MRI), deep learning offers very powerful technical support with significant results. However, the success of supervised learning is strongly dependent on the quantity and accuracy of labeled
Chengcheng Jin +2 more
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Dual Learning-Based Safe Semi-Supervised Learning
IEEE Access, 2018 In many real-world applications, labeled instances are generally limited and expensively collected, while the most instances are unlabeled and the amount is often sufficient.
Haitao Gan +3 more
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AI-Assisted Cotton Grading: Active and Semi-Supervised Learning to Reduce the Image-Labelling Burden
Sensors, 2023 The assessment of food and industrial crops during harvesting is important to determine the quality and downstream processing requirements, which in turn affect their market value. While machine learning models have been developed for this purpose, their
Oliver J. Fisher +4 more
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Semi-Supervised Radio Signal Identification
, 2017 Radio emitter recognition in dense multi-user environments is an important tool for optimizing spectrum utilization, identifying and minimizing interference, and enforcing spectrum policy.
chapelle +9 more
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Advanced Functional Materials, EarlyView.This study introduces a novel multi‐scale scaffold design using L‐fractals arranged in Archimedean tessellations for tissue regeneration. Despite similar porosity, tiles display vastly different tensile responses (1–100 MPa) and deformation modes. In vitro experiments with hMSCs show geometry‐dependent growth and activity. Over 55 000 tile combinations
Maria Kalogeropoulou +4 more
wiley +1 more source
On Ensemble SSL Algorithms for Credit Scoring Problem
Informatics, 2018 Credit scoring is generally recognized as one of the most significant operational research techniques used in banking and finance, aiming to identify whether a credit consumer belongs to either a legitimate or a suspicious customer group.
Ioannis E. Livieris +4 more
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