All Outputs (394)

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..

Inclusive design for immersive spaces. (2019)
Journal Article
CRABB, M., CLARKE, D., ALWAER, H., HERON, M. and LAING, R. 2019. Inclusive design for immersive spaces. Design journal [online], 22(Sup 1: running with scissors: proceedings from 13th European Academy of Design international conference (EAD 2019), 10-12 April 2019, Dundee, UK), pages 2105-2118. Available from: https://doi.org/10.1080/14606925.2019.1594934

It is vital when creating learning environments that attention is paid towards individuals using a given space, activities that they will carry out, and the available equipment that will facilitate this. It is also important that these spaces are cre... Read More about Inclusive design for immersive spaces..

Video tampering localisation using features learned from authentic content. (2019)
Journal Article
JOHNSTON, P., ELYAN, E. and JAYNE, C. 2020. Video tampering localisation using features learned from authentic content. Neural computing and applications [online], 32(16): special issue on Real-world optimization problems and meta-heuristics and selected papers from the 19th Engineering applications of neural networks conference 2018 (EANN 2018), 3-5 September 2018, Bristol UK , pages 12243-12257. Available from: https://doi.org/10.1007/s00521-019-04272-z

Video tampering detection remains an open problem in the field of digital media forensics. As video manipulation techniques advance, it becomes easier for tamperers to create convincing forgeries that can fool human eyes. Deep learning methods have a... Read More about Video tampering localisation using features learned from authentic content..

Calculating the impact of event using emotion detection. (2019)
Journal Article
SHIVA, T., KAVYA, T., REDDY, N.A. and BANO, S. 2019. Calculating the impact of event using emotion detection. International journal of innovative technology and exploring engineering [online], 8(7), article number G5105058719, pages 183-189. Available from: https://www.ijitee.org/portfolio-item/G5105058719/

Regardless of the extraordinary advancements in artificial intelligence, we are still far from having the capacity to normally associate with machines. Feature analysis in emotion recognition is significantly less concentrated than the facial recogni... Read More about Calculating the impact of event using emotion detection..

A fuzzy inference system applied to value of information assessment for oil and gas industry. (2019)
Journal Article
VILELA, M., OLUYEMI, G. and PETROVSKI, A. 2019. A fuzzy inference system applied to value of information assessment for oil and gas industry. Decision making: applications in management and engineering [online], 2(2), pages 1-18. Available from: https:// doi.org/10.31181/dmame1902001v

Value of information is a widely accepted methodology for evaluating the need to acquire new data in the oil and gas industry. In the conventional approach to estimating the value of information, the outcomes of a project assessment relate to the dec... Read More about A fuzzy inference system applied to value of information assessment for oil and gas industry..

Generalised median of graph correspondences. (2019)
Journal Article
MORENO-GARCÍA, C.F. and SERRATOSA, F. 2019. Generalised median of graph correspondences. Pattern recognition letters [online], 125, pages 389-395. Available from: https://doi.org/10.1016/j.patrec.2019.05.015

A graph correspondence is defined as a function that maps the elements of two attributed graphs. Due to the increasing availability of methods to perform graph matching, numerous graph correspondences can be deducted for a pair of attributed graphs.... Read More about Generalised median of graph correspondences..

Hyperspectral image reconstruction using multi-colour and time-multiplexed LED illumination. (2019)
Journal Article
TSCHANNERL, J., REN, J., ZHAO, H., KAO, F.-J., MARSHALL, S. and YUEN, P. 2019. Hyperspectral image reconstruction using multi-colour and time-multiplexed LED illumination. Optics and lasers in engineering [online], 121, pages 352-357. Available from: https://doi.org/10.1016/j.optlaseng.2019.04.014

The rapidly rising industrial interest in hyperspectral imaging (HSI) has generated an increased demand for cost effective HSI devices. We are demonstrating a mobile and low-cost multispectral imaging system, enabled by time-multiplexed RGB Light Emi... Read More about Hyperspectral image reconstruction using multi-colour and time-multiplexed LED illumination..

Coastal wetland mapping with sentinel-2 MSI imagery based on gravitational optimized multilayer perceptron and morphological attribute profiles. (2019)
Journal Article
ZHANG, A., SUN, G., MA, P., JIA, X., REN, J., HUANG, H. and ZHANG, X. 2019. Coastal wetland mapping with sentinel-2 MSI imagery based on gravitational optimized multilayer perceptron and morphological attribute profiles. Remote sensing [online], 11(8), article 952. Available from: https://doi.org/10.3390/rs11080952

Coastal wetland mapping plays an essential role in monitoring climate change, the hydrological cycle, and water resources. In this study, a novel classification framework based on the gravitational optimized multilayer perceptron classifier and exten... Read More about Coastal wetland mapping with sentinel-2 MSI imagery based on gravitational optimized multilayer perceptron and morphological attribute profiles..

Building extraction from high-resolution aerial imagery using a generative adversarial network with spatial and channel attention mechanisms. (2019)
Journal Article
PAN, X., YANG, F., GAO, L., CHEN, Z., ZHANG, B., FAN, H. and REN, J. 2019. Building extraction from high-resolution aerial imagery using a generative adversarial network with spatial and channel attention mechanisms. Remote sensing [online], 11(8), article 917. Available from: https://doi.org/10.3390/rs11080917

Segmentation of high-resolution remote sensing images is an important challenge with wide practical applications. The increasing spatial resolution provides fine details for image segmentation but also incurs segmentation ambiguities. In this paper,... Read More about Building extraction from high-resolution aerial imagery using a generative adversarial network with spatial and channel attention mechanisms..

Understanding factors influencing public transport passengers' pre-travel information-seeking behaviour. (2019)
Journal Article
YEBOAH, G., COTTRILL, C.D., NELSON, J.D., CORSAR, D., MARKOVIC, M. and EDWARDS, P. 2019. Understanding factors influencing public transport passengers’ pre-travel information-seeking behaviour. Public transport [online], 11(1), pages 135-158. Available from: https://doi.org/10.1007/s12469-019-00198-w

This paper investigates factors influencing public transport passengers’ pre-travel information-seeking behaviours in a British urban environment. Public transport traveller surveys were conducted to better understand the journey stages at which info... Read More about Understanding factors influencing public transport passengers' pre-travel information-seeking behaviour..

Flood risk management in sponge cities: the role of integrated simulation and 3D visualization. (2019)
Journal Article
WANG, C., HOU, J., MILLER, D., BROWN, I. and JIANG, Y. 2019. Flood risk management in sponge cities: the role of integrated simulation and 3D visualization. International journal of disaster risk reduction [online], 39, article ID 101139. Available from: https://doi.org/10.1016/j.ijdrr.2019.101139

The Sponge City concept has been promoted as a major programme of work to address increasing flood risk in urban areas, in combination with wider benefits for water resources and urban renewal. However, realization of the concept requires collaborati... Read More about Flood risk management in sponge cities: the role of integrated simulation and 3D visualization..

A weighted multiple classifier framework based on random projection. (2019)
Journal Article
NGUYEN, T.T., DANG, M.T., LIEW, A. W.-C. and BEZDEK, J.C. 2019. A weighted multiple classifier framework based on random projection. Information science [online], 490, pages 36-58. Available from: https://doi.org/10.1016/j.ins.2019.03.067

In this paper, we propose a weighted multiple classifier framework based on random projections. Similar to the mechanism of other homogeneous ensemble methods, the base classifiers in our approach are obtained by a learning algorithm on different tra... Read More about A weighted multiple classifier framework based on random projection..