All Outputs (1100)

Weakly supervised conditional random fields model for semantic segmentation with image patches. (2020)
Journal Article
XU, X., XUE, Y., HAN, X., ZHANG, Z., XIE, J. and REN, J. 2020. Weakly supervised conditional random fields model for semantic segmentation with image patches. Applied sciences [online], 10(5), article 1679. Available from: https://doi.org/10.3390/app10051679

Image semantic segmentation (ISS) is used to segment an image into regions with differently labeled semantic category. Most of the existing ISS methods are based on fully supervised learning, which requires pixel-level labeling for training the model... Read More about Weakly supervised conditional random fields model for semantic segmentation with image patches..

The impact of undergraduate mentorship on student satisfaction and engagement, teamwork performance, and team dysfunction in a software engineering group project. (2020)
Conference Proceeding
IACOB, C. and FAILY, S. 2020. The impact of undergraduate mentorship on student satisfaction and engagement, teamwork performance, and team dysfunction in a software engineering group project. In Proceedings of the 51st ACM technical symposium on computer science education (SIGCSE 2020), 11-14 March 2020, Portland, USA. New York: ACM [online], pages 128-134. Available from: https://doi.org/10.1145/3328778.3366835

Mentorship schemes in software engineering education usually involve professional software engineers guiding and advising teams of undergraduate students working collaboratively to develop a software system. With or without mentorship, teams run the... Read More about The impact of undergraduate mentorship on student satisfaction and engagement, teamwork performance, and team dysfunction in a software engineering group project..

Privacy, security, legal and technology acceptance requirements for a GDPR compliance platform. (2020)
Conference Proceeding
TSOHOU, A., MAGKOS, M., MOURATIDIS, H., CHRYSOLORAS, G., PIRAS, L., PAVLIDIS, M., DEBUSSCHE, J., ROTOLONI, M. and GALLEGO-NICASIO CRESPO, B. 2019. Privacy, security, legal and technology acceptance requirements for a GDPR compliance platform. In Katsikas, S., Cuppens, F., Cuppens, N. et.al (eds.) Computer security: revised and selected papers of 24th European symposium on research in computer security international workshops 2019 (ESORICS 2019), co-located with 5th Security of industrial control systems and cyber-physical systems international workshops (CyberICPS 2019), 3rd Security and privacy requirements engineering international workshops (SECPRE 2019), 1st Security, privacy organizations and systems engineering international workshops (SPOSE 2019) and 2nd Attacks and defences for Internet-of-Things international workshops (ADIoT 2019), 26-27 September 2019, Luxembourg City, Luxembourg. Lecture notes in computer science, 11980. Cham: Springer [online], pages 204- 223. Available from: https://doi.org/10.1007/978-3-030-42048-2_14

GDPR entered into force in May 2018 for enhancing user data protection. Even though GDPR leads towards a radical change with many advantages for the data subjects it turned out to be a significant challenge. Organizations need to make long and comple... Read More about Privacy, security, legal and technology acceptance requirements for a GDPR compliance platform..

Identifying safety and human factors issues in rail using IRIS and CAIRIS. (2020)
Conference Proceeding
ALTAF, A., FAILY, S., DOGAN, H., MYLONAS, A. and THRON, E. 2020. Identifying safety and human factors issues in rail using IRIS and CAIRIS. In Katsikas, S., Cuppens, F., Cuppens, N., Lambrinoudakis, C., Kalloniatis, C., Mylopoulos, J., Antón, A., Gritzalis, S., Pallas, F., Pohle, J., Sasse, A., Meng, W., Furnell, S. and Garcia-Alfaro, J. (eds.) Computer security: ESORICS 2019 international workshops, CyberICPS, SECPRE, SPOSE and ADIoT: revised selected papers from the 5th Workshop on security of industrial control systems and cyber-physical systems (CyberICPS 2019), co-located with the 24th European symposium on research in computer security (ESORICS 2019), 26-27 September 2019, Luxembourg City, Luxembourg. Lecture notes in computer science, 11980. Cham: Springer [online], pages 98-107. Available from: https://doi.org/10.1007/978-3-030-42048-2_7

Security, safety and human factors engineering techniques are largely disconnected although the concepts are interlinked. We present a tool-supported approach based on the Integrating Requirements and Information Security (IRIS) framework using Compu... Read More about Identifying safety and human factors issues in rail using IRIS and CAIRIS..

A knowledge-light approach to personalised and open-ended human activity recognition. (2020)
Journal Article
WIJEKOON, A., WIRATUNGA, N., SANI, S. and COOPER, K. 2020. A knowledge-light approach to personalised and open-ended human activity recognition. Knowledge-based systems [online], 192, article ID 105651. Available from: https://doi.org/10.1016/j.knosys.2020.105651

Human Activity Recognition (HAR) is a core component of clinical decision support systems that rely on activity monitoring for self-management of chronic conditions such as Musculoskeletal Disorders. Deployment success of such applications in part de... Read More about A knowledge-light approach to personalised and open-ended human activity recognition..

Reducing human effort in engineering drawing validation. (2020)
Journal Article
RICA, E., MORENO-GARCÍA, C.F., ÁLVAREZ, S. and SERRATOS, F. 2020. Reducing human effort in engineering drawing validation. Computers in industry [online], 117, article ID 103198. Available from: https://doi.org/10.1016/j.compind.2020.103198

Oil & Gas facilities are extremely huge and have complex industrial structures that are documented using thousands of printed sheets. During the last years, it has been a tendency to migrate these paper sheets towards a digital environment, with the... Read More about Reducing human effort in engineering drawing validation..

Varietal classification of rice seeds using RGB and hyperspectral images. (2020)
Journal Article
FABIYI, S.D., VU, H., TACHTATZIS, C., MURRAY, P., HARLE, D., DAO, T.K., ANDONOVIC, I., REN, J. and MARSHALL, S. 2020. Varietal classification of rice seeds using RGB and hyperspectral images. IEEE access [online], 8, pages 22493-22505. Available from: https://doi.org/10.1109/ACCESS.2020.2969847

Inspection of rice seeds is a crucial task for plant nurseries and farmers since it ensures seed quality when growing seedlings. Conventionally, this process is performed by expert inspectors who manually screen large samples of rice seeds to identif... Read More about Varietal classification of rice seeds using RGB and hyperspectral images..

MIMN-DPP: maximum-information and minimum-noise determinantal point processes for unsupervised hyperspectral band selection. (2020)
Journal Article
CHEN, W., YANG, Z., REN, J., CAO, J., CAI, N., ZHAO, H. and YUEN, P. 2020. MIMN-DPP: maximum-information and minimum-noise determinantal point processes for unsupervised hyperspectral band selection. Pattern recognition [online], 102, article 107213. Available from: https://doi.org/10.1016/j.patcog.2020.107213

Band selection plays an important role in hyperspectral imaging for reducing the data and improving the efficiency of data acquisition and analysis whilst significantly lowering the cost of the imaging system. Without the category labels, it is chall... Read More about MIMN-DPP: maximum-information and minimum-noise determinantal point processes for unsupervised hyperspectral band selection..

Human activity recognition with deep metric learners. (2020)
Conference Proceeding
MARTIN, K., WIJEKOON, A. and WIRATUNGA, N. 2019. Human activity recognition with deep metric learners. In Kapetanakis, S. and Borck, H. (eds.) Proceedings of the 27th International conference on case-based reasoning workshop (ICCBR-WS19), co-located with the 27th International conference on case-based reasoning (ICCBR19), 8-12 September 2019, Otzenhausen, Germany. CEUR workshop proceedings, 2567. Aachen: CEUR-WS [online], pages 8-17. Available from: http://ceur-ws.org/Vol-2567/paper1.pdf

Establishing a strong foundation for similarity-based return is a top priority in Case-Based Reasoning (CBR) systems. Deep Metric Learners (DMLs) are a group of neural network architectures which learn to optimise case representations for similarity-... Read More about Human activity recognition with deep metric learners..

Automatic extraction of water inundation areas using Sentinel-1 data for large plain areas. (2020)
Journal Article
HU, S., QIN, J., REN, J., ZHAO, H., REN, J., and HONG, H. 2020. Automatic extraction of water inundation areas using sentinel-1 data for large plain areas. Remote sensing [online], 12(2), article 243. Available from: https://doi.org/10.3390/rs12020243

Accurately quantifying water inundation dynamics in terms of both spatial distributions and temporal variability is essential for water resources management. Currently, the water map is usually derived from synthetic aperture radar (SAR) data with th... Read More about Automatic extraction of water inundation areas using Sentinel-1 data for large plain areas..

Learning from small and imbalanced dataset of images using generative adversarial neural networks. (2019)
Thesis
ALI-GOMBE, A. 2019. Learning from small and imbalanced dataset of images using generative adversarial neural networks. Robert Gordon University [online], PhD thesis. Available from: https://openair.rgu.ac.uk

The performance of deep learning models is unmatched by any other approach in supervised computer vision tasks such as image classification. However, training these models requires a lot of labeled data, which are not always available. Labelling a ma... Read More about Learning from small and imbalanced dataset of images using generative adversarial neural networks..

Food survey using exploratory data analysis. (2019)
Conference Proceeding
RAMYASRI, R., ISHASANJIDA, S., PARASA, D. and BANO, S. 2019. Food survey using exploratory data analysis. In Proceedings of the 2nd International conference on intelligent communication and computational techniques (ICCT 2019), 28-29 September 2019, Jaipur, India. Piscataway: IEEE [online], pages 258-264. Available from: https://doi.org/10.1109/ICCT46177.2019.8969016

A person's eating habits are the most important aspect of maintaining one's physical wellbeing, which in turn is key to enduring the stresses and emotional hurdles that are so commonplace in our modern lifestyles. Our research shows that, over the pa... Read More about Food survey using exploratory data analysis..

Classification of binary fracture using CNN. (2019)
Conference Proceeding
CHITTAJALLU, S.M., MANDALANENI, N.L.D., PARASA, D. and BANO, S. 2019. Classification of binary fracture using CNN. In Proceedings of the 1st Global conference for advancement in technology (GCAT 2019), 18-20 October 2019, Bangalore, India. Piscataway: IEEE [online]. Available from: https://doi.org/10.1109/GCAT47503.2019.8978468

One of the major problems faced by any living organism since infancy are musculoskeletal injuries. To keep it quite simple musculoskeletal injuries are a range of disorders involving muscles, bones, tendons, blood vessels, nerves and other soft tissu... Read More about Classification of binary fracture using CNN..

Deep heterogeneous ensemble. (2019)
Journal Article
NGUYEN, T.T., DANG, M.T., PHAM, T.D., DAO, L.P., LUONG, A.V., MCCALL, J. and LIEW, A.W.C. 2019. Deep heterogeneous ensemble. Australian journal of intelligent information processing systems [online], 16(1): special issue on neural information processing: proceedings of the 26th International conference on neural information processing (ICONIP 2019), 12-15 December 2019, Sydney, Australia, pages 1-9. Available from: http://ajiips.com.au/papers/V16.1/v16n1_5-13.pdf

In recent years, deep neural networks (DNNs) have emerged as a powerful technique in many areas of machine learning. Although DNNs have achieved great breakthrough in processing images, video, audio and text, it also has some limitations... Read More about Deep heterogeneous ensemble..

Generation and optimisation of real-world static and dynamic location-allocation problems with application to the telecommunications industry. (2019)
Thesis
ANKRAH, R.B. 2019. Generation and optimisation of real-world static and dynamic location-allocation problems with application to the telecommunications industry. Robert Gordon University [online], PhD thesis. Available from: https://openair.rgu.ac.uk

The location-allocation (LA) problem concerns the location of facilities and the allocation of demand, to minimise or maximise a particular function such as cost, profit or a measure of distance. Many formulations of LA problems have been presented i... Read More about Generation and optimisation of real-world static and dynamic location-allocation problems with application to the telecommunications industry..

Food places classification in egocentric images using Siamese neural networks. (2019)
Conference Proceeding
SARKER, M.M.K., BANU, S.F., RASHWAN, H.A., ABDEL-NASSER, M., SINGH, V.K., CHAMBON, S., RADEVA, P. and PUIG, D. 2019. Food places classification in egocentric images using Siamese neural networks. In Sabater-Mir, J., Torra, V., Aguiló, I. and González-Hidalgo, M. (eds.) Artificial intelligence research and development: proceedings of the 22nd International conference of the Catalan Association for Artificial Intelligence (CCIA 2019), 23-25 October 2019, Colònia de Sant Jordi, Spain. Frontiers in artificial intelligence and applications, 319. Amsterdam: IOS Press [online], pages 145-151. Available from: https://doi.org/10.3233/FAIA190117

Wearable cameras have become more popular in recent years for capturing unscripted moments in the first-person, which help in analysis of the user's lifestyle. In this work, we aim to identify the daily food patterns of a person through recognition o... Read More about Food places classification in egocentric images using Siamese neural networks..

Social media survey using decision tree and naive Bayes classification. (2019)
Conference Proceeding
ROSHINI, T., SIREESHA, P.V., PARASA, D. and BANO, S. 2019. Social media survey using decision tree and naive Bayes classification. In Proceedings of the 2nd International conference on intelligent communication and computational techniques (ICCT 2019), 28-29 September 2019, Jaipur, India. Piscataway: IEEE [online], pages 265-270. Available from: https://doi.org/10.1109/ICCT46177.2019.8969058

Social media - a website or an application that is used to create and share content among a social network - is one of the most important aspects of our day-to-day life. Recent studies claim that an average person spends roughly 142 minutes per day o... Read More about Social media survey using decision tree and naive Bayes classification..

Integrating selection-based aspect sentiment and preference knowledge for social recommender systems. (2019)
Journal Article
CHEN, Y.Y., WIRATUNGA, N. and LOTHIAN, R. 2020. Integrating selection-based aspect sentiment and preference knowledge for social recommender systems. Online information review [online], 44(2), pages 399-416. Available from: https://doi.org/10.1108/OIR-02-2017-0066

Purpose: Recommender system approaches such as collaborative and content-based filtering rely on user ratings and product descriptions to recommend products. More recently, recommender system research has focussed on exploiting knowledge from user-ge... Read More about Integrating selection-based aspect sentiment and preference knowledge for social recommender systems..

Evolving an optimal decision template for combining classifiers. (2019)
Conference Proceeding
NGUYEN, T.T., LUONG, A.V., DANG, M.T., DAO, L.P., NGUYEN, T.T.T., LIEW, A.W.-C. and MCCALL, J. 2019. Evolving an optimal decision template for combining classifiers. In Gedeon, T., Wong, K.W. and Lee, M. (eds.) Neural information processing: proceedings of the 26th International conference on neural information processing (ICONIP 2019), 12-15 December 2019, Sydney, Australia. Part I. Lecture notes in computer science, 11953. Cham: Springer [online], pages 608-620. Available from: https://doi.org/10.1007/978-3-030-36708-4_50

In this paper, we aim to develop an effective combining algorithm for ensemble learning systems. The Decision Template method, one of the most popular combining algorithms for ensemble systems, does not perform well when working on certain datasets l... Read More about Evolving an optimal decision template for combining classifiers..

A comparison of feature extractors for panorama stitching in an autonomous car architecture. (2019)
Conference Proceeding
CORTÉS-GALLARDO, E., MORENO-GARCIA, C.F., ZHU, A., CHÍPULI-SILVA, D., GONZÁLEZ-GONZÁLEZ, J.A., MORALES-ORTIZ, D., FERNÁNDEZ, S., URRIZA, B., VALVERDE-LÓPEZ, J., MARÍN, A., PÉREZ, H., IZQUIERDO-REYES, J. and BUSTAMANTE-BELLO, R. 2019. A comparison of feature extractors for panorama stitching in an autonomous care architecture. In Proceedings of 2019 International conference on mechatronics, electronics and automotive engineering (ICMEAE 2019), 26-29 November 2019, Cuernavaca, Mexico. Piscataway: IEEE [online], page 50-55. Available from: https://doi.org/10.1109/ICMEAE.2019.00017

Panorama stitching consists on frames being put together to create a 360o view. This technique is proposed for its implementation in autonomous vehicles instead of the use of an external 360o camera, mostly due to its reduced cost and improved aerody... Read More about A comparison of feature extractors for panorama stitching in an autonomous car architecture..