All Outputs (20)

Automated glaucoma diagnosis using deep learning approach (2017)
Conference Proceeding
Al-Bander, B., Al-Nuaimy, W., Al-Taee, M. A., & Zheng, Y. (2017). Automated glaucoma diagnosis using deep learning approach. . https://doi.org/10.1109/SSD.2017.8166974

Glaucoma is one of the common causes of blindness worldwide. It leads to deterioration in vision and quality of life if it is not cured early. This paper addresses the feasibility of developing an automatic feature learning technique for detecting gl... Read More about Automated glaucoma diagnosis using deep learning approach.

A Robust Data-Driven Approach to the Decoding of Pyloric Neuron Activity (2017)
Conference Proceeding
dos Santos, F., Andras, P., Collins, D. J., & Lam, K. P. (2017). A Robust Data-Driven Approach to the Decoding of Pyloric Neuron Activity. In 2017 IEEE International Workshop on Signal Processing Systems (SiPS). https://doi.org/10.1109/SiPS.2017.8110017

The combination of intra and extra-cellular recording of small neuronal circuits such as stomatogastric nervous systems of the crab (Cancer borealis) is well documented and routinely practised. Voltage sensitive dye imaging (VSDi) is a promising tech... Read More about A Robust Data-Driven Approach to the Decoding of Pyloric Neuron Activity.

Determining Firing Strengths Through a Novel Similarity Measure to Enhance Uncertainty Handling in Non-singleton Fuzzy Logic Systems (2017)
Conference Proceeding
Pekaslan, D., Kabir, S., Garibaldi, J. M., & Wagner, C. (2017). Determining Firing Strengths Through a Novel Similarity Measure to Enhance Uncertainty Handling in Non-singleton Fuzzy Logic Systems. In Proceedings of the 9th International Joint Conference on Computational Intelligence - Volume 0IJCCI (83-90). https://doi.org/10.5220/0006502000830090

Non-singleton Fuzzy Logic Systems have the potential to tackle uncertainty within the design of fuzzy systems. The inference process has a major role in determining results, being partly based on the interaction of input and antecedent fuzzy sets (in... Read More about Determining Firing Strengths Through a Novel Similarity Measure to Enhance Uncertainty Handling in Non-singleton Fuzzy Logic Systems.

Towards an Accurate Identification of Pyloric Neuron Activity with VSDi (2017)
Conference Proceeding
dos Santos, F., Andras, P., & Lam, K. (2017). Towards an Accurate Identification of Pyloric Neuron Activity with VSDi. In Artificial Neural Networks and Machine Learning – ICANN 2017. https://doi.org/10.1007/978-3-319-68600-4_15

Voltage-sensitive dye imaging (VSDi) which enables simultaneous optical recording of many neurons in the pyloric circuit of the stomatogastric ganglion is an important technique to supplement electrophysiological recordings. However, utilising the te... Read More about Towards an Accurate Identification of Pyloric Neuron Activity with VSDi.

A Multiresolution Approach to the Extraction of the Pyloric Rhythm (2017)
Conference Proceeding
dos Santos, F., Andras, P., & Lam, K. P. (2017). A Multiresolution Approach to the Extraction of the Pyloric Rhythm. In 2017 40th International Conference on Telecommunications and Signal Processing (TSP). https://doi.org/10.1109/TSP.2017.8076015

This paper describes our work toward the development of a computationally robust methodology to identify the pyloric neurons in the stomatogastric ganglion of Cancer pagurus using voltage-sensitive dye imaging. The multi-resolution signal decompositi... Read More about A Multiresolution Approach to the Extraction of the Pyloric Rhythm.

I2R VC @ ImageClef2017: Ensemble of Deep Learnt Features for Lifelog Video Summarization (2017)
Conference Proceeding
Molino, A., Mandal, B., Jie, L., Lim, J., Subbaraju, V., & Chandrasekhar, V. (2017). I2R VC @ ImageClef2017: Ensemble of Deep Learnt Features for Lifelog Video Summarization.

In this paper we describe our approach for the ImageCLEF-lifelog summarization task. A total of ten runs were submitted, which used only visual features, only metadata information, or both. In the first step, a set of relevant frames are drawn from t... Read More about I2R VC @ ImageClef2017: Ensemble of Deep Learnt Features for Lifelog Video Summarization.

Fast blur detection and parametric deconvolution of retinal fundus images (2017)
Conference Proceeding
Williams, B. M., Al-Bander, B., Pratt, H., Lawman, S., Zhao, Y., Zheng, Y., & Shen, Y. (2017). Fast blur detection and parametric deconvolution of retinal fundus images. In Lecture Notes in Computer Science (194-201). https://doi.org/10.1007/978-3-319-67561-9_22

Blur is a significant problem in medical imaging which can hinder diagnosis and prevent further automated or manual processing. The problem of restoring an image from blur degradation remains a challenging task in image processing. Semi-blind deblurr... Read More about Fast blur detection and parametric deconvolution of retinal fundus images.

Artificial Neural Network Analysis of Volatile Organic Compounds for the detection of lung cancer (2017)
Conference Proceeding
Butcher, J. B., Rutter, A. V., Wootton, A. J., Day, C. R., & Sulé-Suso, J. (2017). Artificial Neural Network Analysis of Volatile Organic Compounds for the detection of lung cancer. In Advances in Computational Intelligence Systems (183-190). https://doi.org/10.1007/978-3-319-66939-7_15

Lung cancer is a widespread disease and it is well understood that systematic, non-invasive and early detection of this progressive and life-threatening disorder is of vital importance for patient outcomes. In this work we present a convergence of fa... Read More about Artificial Neural Network Analysis of Volatile Organic Compounds for the detection of lung cancer.

Towards Accurate Predictions of Customer Purchasing Patterns (2017)
Conference Proceeding
Valero-Fernandez, R., Collins, D. J., Lam, K., Rigby, C., & Bailey, J. (2017). Towards Accurate Predictions of Customer Purchasing Patterns. In 2017 IEEE International Conference on Computer and Information Technology (CIT). https://doi.org/10.1109/cit.2017.58

A range of algorithms was used to classify online retail customers of a UK company using historical transaction data. The predictive capabilities of the classifiers were assessed using linear regression, Lasso and regression trees. Unlike most relate... Read More about Towards Accurate Predictions of Customer Purchasing Patterns.

An empirical approach for automatic face clustering on personal lifelogging images (2017)
Conference Proceeding
Subbaraju, V., Xu, Q., Mandal, B., Li, L., & Lim, J. (2017). An empirical approach for automatic face clustering on personal lifelogging images. . https://doi.org/10.1109/siprocess.2017.8124519

Life-logging applications generate a vast amount of personalized data that provides vital insights into the user's daily life. One such key insight is the people whom the user has come across/interacted with during regular life. This can be obtained... Read More about An empirical approach for automatic face clustering on personal lifelogging images.

Towards Accurate Predictions of Customer Purchasing Patterns (2017)
Conference Proceeding
Valero-Fernandez, R., Collins, D. J., Lam, K., Rigby, C., & Bailey, J. (2017). Towards Accurate Predictions of Customer Purchasing Patterns. . https://doi.org/10.1109/CIT41763.2017

range of algorithms was used to classify online retail customers of a UK company using historical transaction data. The predictive capabilities of the classifiers were assessed using linear regression, Lasso and regression trees. Unlike most related... Read More about Towards Accurate Predictions of Customer Purchasing Patterns.

A Systematic Mapping Study of Empirical Studies on Software Cloud Testing Methods (2017)
Conference Proceeding
Al-Said Ahmad, A., Brereton, O., & Andras, P. (2017). A Systematic Mapping Study of Empirical Studies on Software Cloud Testing Methods. In 2017 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C). https://doi.org/10.1109/QRS-C.2017.94

Context: Software has become more complicated, dynamic, and asynchronous than ever, making testing more challenging. With the increasing interest in the development of cloud computing, and increasing demand for cloud-based services, it has become ess... Read More about A Systematic Mapping Study of Empirical Studies on Software Cloud Testing Methods.

A Virtual 3D Cuneiform Tablet Reconstruction Interaction (2017)
Conference Proceeding
Hanes, L., Lewis, A., Nash, D., Gehlken, E., Hernandez-Munoz, L., Ch’ng, E., …Collins, T. (2017). A Virtual 3D Cuneiform Tablet Reconstruction Interaction. . https://doi.org/10.14236/ewic/HCI2017.73

Novel similarity measure for interval-valued data based on overlapping ratio (2017)
Conference Proceeding
Kabir, S., Wagner, C., Havens, T. C., Anderson, D. T., & Aickelin, U. (2017). Novel similarity measure for interval-valued data based on overlapping ratio. . https://doi.org/10.1109/fuzz-ieee.2017.8015623

In computing the similarity of intervals, current similarity measures such as the commonly used Jaccard and Dice measures are at times not sensitive to changes in the width of intervals, producing equal similarities for substantially different pairs... Read More about Novel similarity measure for interval-valued data based on overlapping ratio.

A Collaborative Artefact Reconstruction Environment (2017)
Conference Proceeding
Woolley, S. I., Ch’ng, E., Hernandez-Munoz, L., Gehlken, E., Collins, T., Nash, D., …Hanes, L. (2017). A Collaborative Artefact Reconstruction Environment. . https://doi.org/10.14236/ewic/HCI2017.53

A novel collaborative artefact reconstruction environment design is presented that is informed by experimental task observation and participatory design. The motivation for the design was to enable collaborative human and computer effort in the recon... Read More about A Collaborative Artefact Reconstruction Environment.

Computer aided diagnosis of age-related macular degeneration in 3D OCT images by deep learning (2017)
Conference Proceeding
Zheng, Y., Williams, B. M., Pratt, H., Al-Bander, B., Wu, X., & Zhao, Y. (2017). Computer aided diagnosis of age-related macular degeneration in 3D OCT images by deep learning.

Purpose : Three-dimensional (3D) optical coherence tomography (OCT) images are increasingly used in the management of eye disease, yet there has been no corresponding increase in the availability of software tools to support the analysis of large amo... Read More about Computer aided diagnosis of age-related macular degeneration in 3D OCT images by deep learning.

Using supervised machine learning algorithms to detect suspicious URLs in online social networks (2017)
Conference Proceeding
Al-Janabi, M., de Quincey, E., & Andras, P. (2017). Using supervised machine learning algorithms to detect suspicious URLs in online social networks. . https://doi.org/10.1145/3110025.3116201

Visual Augmentation Glasses for People with Impaired Vision (2017)
Conference Proceeding
Al-Ataby, A., Younis, O., Al-Nuaimy, W., Al-Taee, M., Sharaf, Z., & Al-Bander, B. (2017). Visual Augmentation Glasses for People with Impaired Vision. . https://doi.org/10.1109/DeSE.2016.6

This paper presents the preliminary design and development of a set visual augmentation glasses with the potential to assist people with varying degrees of loss of vision. The wearable spectacles are intended to be non-obstructive, and therefore empl... Read More about Visual Augmentation Glasses for People with Impaired Vision.

Automatic Feature Learning Method for Detection of Retinal Landmarks (2017)
Conference Proceeding
Al-Bander, B., Al-Nuaimy, W., Al-Taee, M. A., Al-Ataby, A., & Zheng, Y. (2017). Automatic Feature Learning Method for Detection of Retinal Landmarks. . https://doi.org/10.1109/DeSE.2016.4

This paper presents an automatic deep learning method for location detection of important retinal landmarks, the fovea and optic disc (OD) in digital fundus retinal images with the potential for use in an automated screening and grading system. The p... Read More about Automatic Feature Learning Method for Detection of Retinal Landmarks.

Analysis of Human Attentions for Face Recognition on Natural Videos and Comparison with CV Algorithm on Performance (2017)
Conference Proceeding
Ragab Sayed, M., Yuting Lim, R., Mandal, B., Li, L., Hwee Lim, J., & Sim, T. (2017). Analysis of Human Attentions for Face Recognition on Natural Videos and Comparison with CV Algorithm on Performance. In No. 7: Science of Intelligence: Computational Principles of Natural and Artificial Intelligence

Researchers have conducted many studies on human attentions and their eye gaze patterns for face recognition (FR), hoping to inspire new ideas to develop computer vision (CV) algorithms which perform like or even better than human. Yet, while these s... Read More about Analysis of Human Attentions for Face Recognition on Natural Videos and Comparison with CV Algorithm on Performance.