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Search results for: federated learning , breast cancer , health industry , image classification , mammography , deep learning
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Electronic Journal of e-Learning
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International Journal of Learning Technology
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Active Learning in Higher Education
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Learning Disabilities-A Multidisciplinary Journal
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Australian Journal of Learning Difficulties
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IEEE Transactions on Learning Technologies
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Journal of Unschooling and Alternative Learning
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Psychology Learning and Teaching-PLAT
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Tizard Learning Disability Review
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New Directions for Teaching and Learning
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Advances in Learning and Behavioral Disabilities
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Malaysian Journal of Learning & Instruction
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International Journal of Technologies in Learning
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Journal of Motor Learning and Development
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CONTINUUM Lifelong Learning in Neurology
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E-Learning and Digital Media
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JOURNAL OF COMPUTER ASSISTED LEARNING
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Improving Accuracy of Contactless Respiratory Rate Estimation by Enhancing Thermal Sequences with Deep Neural Networks
PublicationEstimation of vital signs using image processing techniques have already been proved to have a potential for supporting remote medical diagnostics and replacing traditional measurements that usually require special hardware and electrodes placed on a body. In this paper, we further extend studies on contactless Respiratory Rate (RR) estimation from extremely low resolution thermal imagery by enhancing acquired sequences using Deep...
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Flexible Knowledge–Vision–Integration Platform for Personal Protective Equipment Detection and Classification Using Hierarchical Convolutional Neural Networks and Active Leaning
PublicationThis work is part of an effort to develop of a Knowledge-Vision Integration Platform for Hazard Control (KVIP-HC) in industrial workplaces, adaptable to a wide range of industrial environments. The paper focuses on hazards resulted from the non-use of personal protective equipment (PPE). The objective is to test the capability of the platform to adapt to different industrial environments by simulating the process of randomly selecting...
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Robust-adaptive dynamic programming-based time-delay control of autonomous ships under stochastic disturbances using an actor-critic learning algorithm
PublicationThis paper proposes a hybrid robust-adaptive learning-based control scheme based on Approximate Dynamic Programming (ADP) for the tracking control of autonomous ship maneuvering. We adopt a Time-Delay Control (TDC) approach, which is known as a simple, practical, model free and roughly robust strategy, combined with an Actor-Critic Approximate Dynamic Programming (ACADP) algorithm as an adaptive part in the proposed hybrid control...
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INFLUENCE OF DATA NORMALIZATION ON THE EFFECTIVENESS OF NEURAL NETWORKS APPLIED TO CLASSIFICATION OF PAVEMENT CONDITIONS – CASE STUDY
PublicationIn recent years automatic classification employing machine learning seems to be in high demand for tele-informatic-based solutions. An example of such solutions are intelligent transportation systems (ITS), in which various factors are taken into account. The subject of the study presented is the impact of data pre-processing and normalization on the accuracy and training effectiveness of artificial neural networks in the case...
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Cancer-selective, single agent chemoradiosensitising gold nanoparticles
PublicationTwo nanometre gold nanoparticles (AuNPs), bearing sugar moieties and/or thiol-polyethylene glycol-amine (PEG-amine), were synthesised and evaluated for their in vitro toxicity and ability to radiosensitise cells with 220 kV and 6 MV X-rays, using four cell lines representing normal and cancerous skin and breast tissues. Acute 3 h exposure of cells to AuNPs, bearing PEG-amine only or a 50:50 ratio of alpha-galactose derivative and...
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Tuning of the Anti-Breast Cancer Activity of Betulinic Acid via Its Conversion to Ionic Liquids
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Biological effects in photodynamic treatment combined with electropermeabilization in wild and drug resistant breast cancer cells
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A different methylation profile of circadian genes promoter in breast cancer patients according to clinicopathological features
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Nanofiltration in the food industry
PublicationNanofiltration (NF), as a pressure-driven membrane process, has been widely demonstrated to have great potential for food processing applications. There are several advantages of this membrane process over traditional methods that makes NF suitable for food processing, such as the low thermal damage to the product, higher aroma retention, lower energy consumption, and low maintenance costs. In this chapter, according to the recent...
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Higher platelet counts correlate to tumour progression and can be induced by intratumoural stroma in non-metastatic breast carcinomas
PublicationBackground Platelets support tumour progression. However, their prognostic significance and relation to circulating tumour cells (CTCs) in operable breast cancer (BrCa) are still scarcely known and, thus, merit further investigation. Methods Preoperative platelet counts (PCs) were compared with clinical data, CTCs, 65 serum cytokines and 770 immune-related transcripts obtained using the NanoString technology. Results High normal...
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Framework for Structural Health Monitoring of Steel Bridges by Computer Vision
PublicationThe monitoring of a structural condition of steel bridges is an important issue. Good condition of infrastructure facilities ensures the safety and economic well-being of society. At the same time, due to the continuous development, rising wealth of the society and socio-economic integration of countries, the number of infrastructural objects is growing. Therefore, there is a need to introduce an easy-to-use and relatively low-cost...
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Learning Feedforward Control Using Multiagent Control Approach for Motion Control Systems
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Learning from Imbalanced Data Streams Based on Over-Sampling and Instance Selection
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Machine Learning and data mining tools applied for databases of low number of records
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Simulation Method for Scheduling Linear Construction Projects Using the Learning– Forgetting Effect
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Multivariate Features Extraction and Effective Decision Making Using Machine Learning Approaches
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Machine learning techniques combined with dose profiles indicate radiation response biomarkers
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