All Outputs (59)

Landscape features and automated algorithm selection for multi-objective interpolated continuous optimisation problems. (2021)
Conference Proceeding
LIEFOOGHE, A., VEREL, S., LACROIX, B., ZĂVOIANU, A.-C. and MCCALL, J. 2021. Landscape features and automated algorithm selection for multi-objective interpolated continuous optimisation problems. In Chicano, F. (ed) Proceedings of 2021 Genetic and evolutionary computation conference (GECCO 2021), 10-14 July 2021, [virtual conference]. New York: ACM [online], pages 421-429. Available from: https://doi.org/10.1145/3449639.3459353

In this paper, we demonstrate the application of features from landscape analysis, initially proposed for multi-objective combinatorial optimisation, to a benchmark set of 1 200 randomly-generated multiobjective interpolated continuous optimisation p... Read More about Landscape features and automated algorithm selection for multi-objective interpolated continuous optimisation problems..

Non-deterministic solvers and explainable AI through trajectory mining. (2021)
Conference Proceeding
FYVIE, M., MCCALL, J.A.W. and CHRISTIE, L.A. 2021. Non-deterministic solvers and explainable AI through trajectory mining. In Martin, K., Wiratunga, N. and Wijekoon, A. (eds.) SICSA XAI workshop 2021: proceedings of 2021 SICSA (Scottish Informatics and Computer Science Alliance) eXplainable artificial intelligence workshop (SICSA XAI 2021), 1st June 2021, [virtual conference]. CEUR workshop proceedings, 2894. Aachen: CEUR-WS [online], session 4, pages 75-78. Available from: http://ceur-ws.org/Vol-2894/poster2.pdf

Traditional methods of creating explanations from complex systems involving the use of AI have resulted in a wide variety of tools available to users to generate explanations regarding algorithm and network designs. This however has traditionally bee... Read More about Non-deterministic solvers and explainable AI through trajectory mining..

VEGAS: a variable length-based genetic algorithm for ensemble selection in deep ensemble learning. (2021)
Conference Proceeding
HAN, K., PHAM, T., VU, T.H., DANG, T., MCCALL, J. and NGUYEN, T.T. 2021. VEGAS: a variable length-based genetic algorithm for ensemble selection in deep ensemble learning. In Nguyen, N.T., Chittayasothorn, S., Niyato, D. and Trawiński, B. (eds.) Intelligent information and database systems: proceedings of the 13th Asian conference on intelligent information and database systems 2021 (ACCIIDS 2021), 7-10 April 2021, [virtual conference]. Lecture Notes in Computer Science, 12672. Cham: Springer [online], pages 168–180. Available from: https://doi.org/10.1007/978-3-030-73280-6_14

In this study, we introduce an ensemble selection method for deep ensemble systems called VEGAS. The deep ensemble models include multiple layers of the ensemble of classifiers (EoC). At each layer, we train the EoC and generates training data for th... Read More about VEGAS: a variable length-based genetic algorithm for ensemble selection in deep ensemble learning..

Health state classification of a spherical tank using a hybrid bag of features and k-nearest neighbor. (2021)
Conference Proceeding
HASAN, M.J., KIM, J. and KIM, J.-M. 2021. Health state classification of a spherical tank using a hybrid bag of features and k-nearest neighbor. In Park, J.J., Fong, S.J., Pan, Y. and Sung, Y. (eds.) Advances in computer science and ubiquitous computing: proceedings of the 11th International conference on computer science and its applications (CSA 2019), and the 14th KIPS international conference on ubiquitous information technologies and applications (CUTE) 2019) (CSA-CUTE 2019), 18-20 December 2019, Macau, China. Lecture notes in electrical engineering, 715. Singapore: Springer [online], pages 235-241. Available from: https://doi.org/10.1007/978-981-15-9343-7_32

Feature analysis plays an important role in determining the various health conditions of mechanical vessels. To achieve balance between traditional feature extraction and the automated feature selection process, a hybrid bag of features (HBoF) is des... Read More about Health state classification of a spherical tank using a hybrid bag of features and k-nearest neighbor..

In-house deep environmental sentience for smart homecare solutions toward ageing society. (2020)
Conference Proceeding
EASOM, P., BOURIDANE, A., QIANG, F., DOWNS, C. and JIANG, R. 2020. In-house deep environmental sentience for smart homecare solutions toward ageing society. In Proceedings of 2020 International conference machine learning and cybernetics (ICMLC 2020), 4 December 2020, [virtual conference]. Piscataway: IEEE [online], pages 261-266. Available from: https://doi.org/10.1109/ICMLC51923.2020.9469531

With an increasing amount of elderly people needing home care around the clock, care workers are not able to keep up with the demand of providing maximum support to those who require it. As medical costs of home care increase the quality is care suff... Read More about In-house deep environmental sentience for smart homecare solutions toward ageing society..

Object recognition using enhanced particle swarm optimization. (2020)
Conference Proceeding
WILLIS, M., ZHANG, L., LIU, H., XIE, H. and MISTRY, L. 2020. Object recognition using enhanced particle swarm optimization. In Proceedings of 2020 International conference machine learning and cybernetics (ICMLC 2020), 4 December 2020, [virtual conference]. Piscataway: IEEE [online], pages 241-246. Available from: https://doi.org/10.1109/ICMLC51923.2020.9469584

The identification of the most discriminative features in an explainable AI decision-making process is a challenging problem. This research tackles such challenges by proposing Particle Swarm Optimization (PSO) variants embedded with novel mutation a... Read More about Object recognition using enhanced particle swarm optimization..

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..

Deep convolutional neural network with 2D spectral energy maps for fault diagnosis of gearboxes under variable speed. (2019)
Conference Proceeding
HASAN, M.J. and KIM, J. 2020. Deep convolutional neural network with 2D spectral energy maps for fault diagnosis of gearboxes under variable speed. In Djeddi, C., Jamil, A. and Siddiqi, I. (eds.) Pattern recognition and artificial intelligence: proceedings of the 3rd Mediterranean conference on pattern recognition and artificial intelligence (MedPRAI 2019), 22-23 December 2019, Istanbul, Turkey. Communications in computer and information science (CCIS), 1144. Cham: Springer [online], pages 106-117. Available from: https://doi.org/10.1007/978-3-030-37548-5_9

For industrial safety, correct classification of gearbox fault conditions is necessary. One of the most crucial tasks in data-driven fault diagnosis is determining the best set of features by analyzing the statistical parameters of the signals. Howev... Read More about Deep convolutional neural network with 2D spectral energy maps for fault diagnosis of gearboxes under variable speed..

VIP-STB farm: scale-up village to county/province level to support science and technology at backyard (STB) program. (2019)
Conference Proceeding
YAN, Y., ZHAO, S., FANG, Y., LIU, Y., CHEN, Z. and REN, J. 2020. VIP-STB farm: scale-up village to county/province level to support science and technology at backyard (STB) program. In Ren, J., Hussain, A., Zhao, H., Huang, K., Zheng, J., Cai, J., Chen, R. and Xiao, Y. (eds.). 2020. Advances in brain inspired cognitive systems: proceedings of the 10th Brain inspired cognitive systems (BCIS) international conference 2019 (BCIS 2019), 13-14 July 2019, Guangzhou, China. Lecture notes in computer science, 11691. Cham: Springer [online], pages 283-292. Available from: https://doi.org/10.1007/978-3-030-39431-8_27

In this paper, we introduce a new concept in VIP-STB, a funded project through Agri-Tech in China: Newton Network+ (ATCNN), in developing feasible solutions towards scaling-up STB from village level to upper level via some generic models and systems.... Read More about VIP-STB farm: scale-up village to county/province level to support science and technology at backyard (STB) program..

FinSeg: finger parts semantic segmentation using multi-scale feature maps aggregation of FCN. (2019)
Conference Proceeding
SALEH, A., RASHWAN, H., ABDEL-NASSER, M., SINGH, V., ABDULWAHAB, S., SARKER, M., GARCIA, M. and PUIG, D. 2019. FinSeg: finger parts semantic segmentation using multi-scale feature maps aggregation of FCN. In Tremeau, A., Farinella, G.M. and Braz, J. (eds.). Proceedings of 14th international joint conferences on Computer vision, imaging and computer graphics theory and applications 2019 (VISIGRAPP 2019), 25-27 February 2019, Prague, Czech Republic. Setúbal, Portugal: SciTePress [online], 5, pages 77-84. Available from: https://doi.org/10.5220/0007382100770084

Image semantic segmentation is in the center of interest for computer vision researchers. Indeed, huge number of applications requires efficient segmentation performance, such as activity recognition, navigation, and human body parsing, etc. One of t... Read More about FinSeg: finger parts semantic segmentation using multi-scale feature maps aggregation of FCN..

Brain MR image segmentation using multiphase active contours based on local and global fitted images. (2018)
Conference Proceeding
AKRAM, F., SINGH, V.K., SARKER, M.M.K., GARCIA, M.A. and PUIG, D. 2018. Brain MR image segmentation using multiphase active contours based on local and global fitter images. In Falomir, Z., Gilbert, K. and Plaza, E. (eds.). Artificial intelligence research and development: current challenges, new trends and applications; contributions from 21st international conference of Catalan Association for Artificial Intelligence 2018 (CCIA 2018), 8-10 October 2018, Alt Empordà, Spain. Frontiers in artificial intelligence and applications, 308. Amsterdam: IOP Press [online], pages 325-334. Available from: https://doi.org/10.3233/978-1-61499-918-8-325

The study of white matter (WM), grey matter (GM) and cerebrospinal fluid (CSF) regions in the brain magnetic resonance (MR) images can be useful for determining different brain disorders, assisting brain surgery, post-surgical analysis, saliency dete... Read More about Brain MR image segmentation using multiphase active contours based on local and global fitted images..

Deep Learning Based Single Image Super-Resolution: A Survey (2018)
Conference Proceeding
HA, V.K., REN, J., XU, X., ZHAO, S. XIE, G. and VARGAS, V.M. 2018. Deep learning based single image super-resolution: a survey. In Ren, J., Hussain, A., Zheng, J., Liu, C.-L., Luo, B., Zhao, H. and Zhao, X. (eds.) Advances in brain inspired cognitive systems: proceedings of 9th International conference brain inspired cognitive systems 2018 (BICS 2018), 7-8 July 2018, Xi'an, China. Lecture notes in computer sciences, 10989. Cham: Springer [online], pages 106-119. Available from: https://doi.org/10.1007/978-3-030-00563-4_11

Image super-resolution is a process of obtaining one or more high-resolution image from single or multiple samples of low-resolution images. Due to its wide applications, a number of different techniques have been developed recently, including interp... Read More about Deep Learning Based Single Image Super-Resolution: A Survey.

Making industrial robots smarter with adaptive reasoning and autonomous thinking for real-time tasks in dynamic environments: a case study. (2018)
Conference Proceeding
ZABALZA, J., FEI, Z., WONG, C., YAN, Y., MINEO, C., YANG, E., RODDEN, T., MEHNEN, J., PHAM, Q.-C. and REN, J. 2018. Making industrial robots smarter with adaptive reasoning and autonomous thinking for real-time tasks in dynamic environments: a case study. In Ren, J., Hussain, A., Zheng, J., Liu, C.-L., Lou, B., Zhao, H. and Zhao, X. (eds.) Advances in brain inspired cognitive systems: proceedings of 9th International conference on Brain inspired cognitive system 2018 (BICS2018), 7-8 July 2018, Xi'an, China. Lecture notes in computer science, 10989. Cham: Springer [online], pages 790-800. Available from: https://doi.org/10.1007/978-3-030-00563-4_77

In order to extend the abilities of current robots in industrial applications towards more autonomous and flexible manufacturing, this work presents an integrated system comprising real-time sensing, path-planning and control of industrial robots to... Read More about Making industrial robots smarter with adaptive reasoning and autonomous thinking for real-time tasks in dynamic environments: a case study..

SLSDeep: Skin Lesion Segmentation Based on Dilated Residual and Pyramid Pooling Networks (2018)
Conference Proceeding
SARKER, M.M.K., RASHWAN, H.A., AKRAM, F., BANU, S.F., SALEH, A., SINGH, V.K., CHOWDHURY, F.U.H., ABDULWAHAB, S., ROMANI, S., RADEVA, P. and PUIG, D. 2018. SLSDeep: skin lesion segmentation based on dilated residual and pyramid pooling networks. In Frangi, A.F., Schnabel, J.A., Davatzikos, C., Alberola-López, C. and Fictinger, G. (eds.) Medical image computing and computer assisted intervention (MICCAI 2018): proceedings of 21st international conference on Medical image computing and computer assisted interventions 2018 (MICCAI 2018), 16-20 September 2018, Granada, Spain. Lecture notes in computer science, 11071. Cham: Springer [online], pages 21-29. Available from: https://doi.org/10.1007/978-3-030-00934-2_3

Skin lesion segmentation (SLS) in dermoscopic images is a crucial task for automated diagnosis of melanoma. In this paper, we present a robust deep learning SLS model represented as an encoder-decoder network. The encoder network is constructed by di... Read More about SLSDeep: Skin Lesion Segmentation Based on Dilated Residual and Pyramid Pooling Networks.

Conditional generative adversarial and convolutional networks for X-ray breast mass segmentation and shape classification. (2018)
Conference Proceeding
SINGH, V.K., ROMANI, S., RASHWAN, H.A., AKRAM, F., PANDEY, N., SARKER, M.M.K., ABDULWAHAB, S., TORRENTS-BARRENA, J., SALEH, A., ARQUEZ, M., ARENAS, M. and PUIG, D. 2018. Conditional generative adversarial and convolutional networks for X-ray breast mass segmentation and shape classification. In Frangi, A.F., Schnabel, J.A., Davatzikos, C., Alberola-López, C. and Fictinger, G. (eds.) Medical image computing and computer assisted intervention (MICCAI 2018): proceedings of 21st international conference on Medical image computing and computer assisted interventions 2018 (MICCAI 2018), 16-20 September 2018, Granada, Spain. Lecture notes in computer science, 11071. Cham: Springer [online], pages 833-840. Available from: https://doi.org/10.1007/978-3-030-00934-2_92

This paper proposes a novel approach based on conditional Generative Adversarial Networks (cGAN) for breast mass segmentation in mammography. We hypothesized that the cGAN structure is well-suited to accurately outline the mass area, especially when... Read More about Conditional generative adversarial and convolutional networks for X-ray breast mass segmentation and shape classification..

Deep visual embedding for image classification. (2018)
Conference Proceeding
SALEH, A., ABDEL-NASSER, M., SARKER, M.M.K., SINGH, V.K., ABDULWAHAB, S., SAFFARI, N., GARCIA, M.A. and PUIG, D. 2018. Deep visual embedding for image classification. In Proceedings of 2018 international conference on Innovative trends in computer engineering (ITCE 2018), 19-21 February 2018, Aswan, Egypt. Piscataway: IEEE [online], pages 31-35. Available from: https://doi.org/10.1109/ITCE.2018.8316596

This paper proposes a new visual embedding method for image classification. It goes further in the analogy with textual data and allows us to read visual sentences in a certain order as in the case of text. The proposed method considers the spatial r... Read More about Deep visual embedding for image classification..

A novel modified SFTA approach for feature extraction. (2016)
Conference Proceeding
HASAN, M.J., UDDIN, J. and PINKU, S.N. 2016. A novel modified SFIA approach for feature extraction. In Proceedings of 3rd International conference on electrical engineering and information and communication technology 2016 (iCEEiCT 2016), 22-24 September 2016, Dhaka, Bangladesh. Piscataway: IEEE [online], article 7873115. Available from: https://doi.org/10.1109/CEEICT.2016.7873115

To increase the efficiency of conventional Segmentation Based Fractal Texture Analysis (SFTA), we propose a new approach on SFTA algorithm. We use an optimum multilevel thresholding hybrid method of Genetic Algorithm (GA) and Particle Swarm Optimizat... Read More about A novel modified SFTA approach for feature extraction..

A novel license plate character segmentation method for different types of vehicle license plates. (2014)
Conference Proceeding
SARKER, M.M.K. and SONG, M.K. 2014. A novel license plate character segmentation method for different types of vehicle license plates. In Proceedings of 2014 International conference on Information and communication technology convergence (ICTC 2014): ICT convergence towards hyper-connected society, 22-24 October 2014, Busan, South Korea. Piscataway: IEEE [online], pages 84-88. Available from: https://doi.org/10.1109/ictc.2014.6983089

License plate character segmentation (LPCS) is a very important part of vehicle license plate recognition (LPR) system. The accuracy of LPR system widely depends on two parts; namely license plate detection (LPD) and LPCS. Different country has diffe... Read More about A novel license plate character segmentation method for different types of vehicle license plates..

Embedded workbench application of GPS sensor for agricultural tractor. (2012)
Conference Proceeding
SARKER, M.M.K., PARK, D., HAM, W., TUMENJARGAL, E. and LEE, J. 2012. Embedded workbench application of GPS sensor for agricultural tractor. In Arabnia, H.R., Deligiannidis, L. and Solo, A.M.G. (eds) Proceedings of the 2012 Embedded systems and applications international conference (ESA'12), 25-28 July 2012, Las Vegas, USA. Athens, GA: CSREA Press. Hosted by WorldComp proceedings [online], pages 40-45. Available from: http://www.worldcomp-proceedings.com/proc/proc2012/esa/papers.pdf

This paper presents a design of an embedded workbench application of Global Positioning System (GPS) for agricultural tractor. Electronic Control Unit (ECU) is Global Positioning System (GPS) sensor using IAR (IAR Embedded Workbench) and an open sour... Read More about Embedded workbench application of GPS sensor for agricultural tractor..