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Exploring the gap between the student expectations and the reality of teamwork in undergraduate software engineering group projects. (2019)
Journal Article
IACOB, C. and FAILY, S. 2019. Exploring the gap between the student expectations and the reality of teamwork in undergraduate software engineering group projects. Journal of systems and software [online], 157, article number 110393. Available from: https://doi.org/10.1016/j.jss.2019.110393

Software engineering group projects aim to provide a nurturing environment for learning about teamwork in software engineering. Since social and teamwork issues have been consistently identified as serious problems in such projects, we aim to better... Read More about Exploring the gap between the student expectations and the reality of teamwork in undergraduate software engineering group projects..

Breast tumor segmentation and shape classification in mammograms using generative adversarial and convolutional neural network. (2019)
Journal Article
SINGH, V.K., RASHWAN, H.A., ROMANI, S., AKRAM, F., PANDEY, N., SARKER, M.M.K., SALEH, A., ARENAS, M., ARQUEZ, M., PUIG, D. and TORRENTS-BARRENA, J. 2020. Breast tumor segmentation and shape classification in mammograms using generative adversarial and convolutional neural network. Expert systems with applications [online], 139, article number 112855. Available from: https://doi.org/10.1016/j.eswa.2019.112855

Mammogram inspection in search of breast tumors is a tough assignment that radiologists must carry out frequently. Therefore, image analysis methods are needed for the detection and delineation of breast tumors, which portray crucial morphological in... Read More about Breast tumor segmentation and shape classification in mammograms using generative adversarial and convolutional neural network..

Deep learning based single image super-resolution: a survey. (2019)
Journal Article
HA, V.K., REN, J.-C., XU, X.-Y., ZHAO, S., XIE, G., MASERO, V. and HUSSAIN, A. 2019. Deep learning based single image super-resolution: a survey. International journal of automation and computing [online], 16(4), pages 413-426. Available from: https://doi.org/10.1007/s11633-019-1183-x

Single image super-resolution has attracted increasing attention and has a wide range of applications in satellite imaging, medical imaging, computer vision, security surveillance imaging, remote sensing, objection detection, and recognition. Recentl... Read More about Deep learning based single image super-resolution: a survey..

MFC-GAN: class-imbalanced dataset classification using multiple fake class generative adversarial network. (2019)
Journal Article
ALI-GOMBE, A. and ELYAN, E. 2019. MFC-GAN: class-imbalanced dataset classification using multiple fake class generative adversarial network. Neurocomputing [online], 361, pages 212-221. Available from: https://doi.org/10.1016/j.neucom.2019.06.043

Class-imbalanced datasets are common across different domains such as health, banking, security and others. With such datasets, the learning algorithms are often biased toward the majority class-instances. Data Augmentation is a common approach tha... Read More about MFC-GAN: class-imbalanced dataset classification using multiple fake class generative adversarial network..

Potential identification and industrial evaluation of an integrated design automation workflow. (2019)
Journal Article
ENTNER, D., PRANTE, T., VOSGIEN, T., ZAVOIANU, A.-C., SAMINGER-PLATZ, S., SCHWARZ, M. and FINK, K. 2019. Potential identification and industrial evaluation of an integrated design automation workflow. Journal of engineering, design and technology [online], 17(6), pages 1085-1109. Available from: https://doi.org/10.1108/JEDT-06-2018-0096

Purpose - The paper aims to raise awareness in the industry of design automation tools, especially in early design phases, by demonstrating along a case study the seamless integration of a prototypically implemented optimization, supporting design sp... Read More about Potential identification and industrial evaluation of an integrated design automation workflow..

Fuzzy logic applied to value of information assessment in oil and gas projects. (2019)
Journal Article
VILELA, M., OLUYEMI, G. and PETROVSKI, A. 2019. Fuzzy logic applied to value of information assessment in oil and gas projects. Petroleum science [online], 16(5), pages 1208-1220. Available from: https://doi.org/10.1007/s12182-019-0348-0

The concept of value of information (VOI) has been widely used in the oil industry when making decisions on the acquisition of new data sets for the development and operation of oil fields. The classical approach to VOI assumes that the outcome of th... Read More about Fuzzy logic applied to value of information assessment in oil and gas projects..

An efficient face recognition system using local binary pattern. (2019)
Journal Article
VISHAL, P., SNIGDHA, L.K. and BANO, S. 2019. An efficient face recognition system using local binary pattern. International journal of recent technology and engineering [online], 8(1S4), article number A11680681S419, pages 912-914. Available from: https://www.ijrte.org/portfolio-item/A11680681S419/

Facial recognition is a critical and prominent aspect of current research into image processing and computer vision, with particular applications including confront location, confront acknowledgement and outward appearance investigation. A basic adva... Read More about An efficient face recognition system using local binary pattern..

A normative decision-making model for cyber security. (2019)
Journal Article
M'MANGA, A., FAILY, S., MCALANEY, J., WILLIAMS, C., KADOBAYASHI, Y. and MIYAMOTO, D. 2019. A normative decision-making model for cyber security. Information and computer security [online], 27(5), pages 636-646. Available from: https://doi.org/10.1108/ICS-01-2019-0021

The purpose of this paper is to investigate security decision-making during risk and uncertain conditions, and to propose a normative model capable of tracing the decision rationale. The proposed risk rationalisation model is grounded in literature a... Read More about A normative decision-making model for cyber security..

Hierarchical approach to classify food scenes in egocentric photo-streams. (2019)
Journal Article
MARTINEZ, E.T., LEYVA-VALLINA, M., SARKER, M.M.K., PUIG, D., PETKOV, N. and RADEVA, P. 2020. Hierarchical approach to classify food scenes in egocentric photo-streams. IEEE journal of biomedical and health informatics [online], 24(3), pages 866-877. Available from: https://doi.org/10.1109/JBHI.2019.2922390

Recent studies have shown that the environment where people eat can affect their nutritional behavior. In this paper, we provide automatic tools for personalized analysis of a person's health habits by the examination of daily recorded egocentric pho... Read More about Hierarchical approach to classify food scenes in egocentric photo-streams..

Multi-label classification via incremental clustering on an evolving data stream. (2019)
Journal Article
NGUYEN, T.T., DANG, M.T., LUONG, A.V., LIEW, A. W.-C., LIANG, T. and MCCALL, J. 2019. Multi-label classification via incremental clustering on an evolving data stream. Pattern recognition [online], 95, pages 96-113. Available from: https://doi.org/10.1016/j.patcog.2019.06.001

With the advancement of storage and processing technology, an enormous amount of data is collected on a daily basis in many applications. Nowadays, advanced data analytics have been used to mine the collected data for useful information and make pred... Read More about Multi-label classification via incremental clustering on an evolving data stream..