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All Outputs (204)

Spontaneous Versus Posed Smiles—Can We Tell the Difference? (2016)
Presentation / Conference Contribution
Mandal, B., & Ouarti, N. (2016, February). Spontaneous Versus Posed Smiles—Can We Tell the Difference?. Presented at International Conference on Computer Vision and Image Processing - CVIP 2016, IIT Roorkee, Roorkee India

Smile is an irrefutable expression that shows the physical state of the mind in both true and deceptive ways. Generally, it shows happy state of the mind, however, ‘smiles’ can be deceptive, for example people can give a smile when they feel happy an... Read More about Spontaneous Versus Posed Smiles—Can We Tell the Difference?.

Appearance based robot activity recognition system (2016)
Presentation / Conference Contribution
Mandal, B. (2016, November). Appearance based robot activity recognition system. Presented at 2016 14th International Conference on Control, Automation, Robotics and Vision (ICARCV), Phuket, Thailand

Face recognition: Perspectives from the real world (2016)
Presentation / Conference Contribution
Mandal, B. (2016, November). Face recognition: Perspectives from the real world. Presented at 2016 14th International Conference on Control, Automation, Robotics and Vision (ICARCV), Phuket, Thailand

In this paper, we analyze some of our real-world deployment of face recognition (FR) systems for various applications and discuss the gaps between expectations of the user and what the system can deliver. We evaluate some of the existing algorithms w... Read More about Face recognition: Perspectives from the real world.

Using Convolutional Neural Network for Edge Detection in Musculoskeletal Ultrasound Images (2016)
Presentation / Conference Contribution
Jabbar, S. I., Day, C. R., Heinz, N., & Chadwick, E. K. (2016, July). Using Convolutional Neural Network for Edge Detection in Musculoskeletal Ultrasound Images. Presented at International Joint Conference on Neural Networks, Vancouver

Fast and accurate segmentation of musculoskeletal ultrasound images is an on-going challenge. Two principal factors make this task difficult: firstly, the presence of speckle noise arising from the interference that accompanies all coherent imaging a... Read More about Using Convolutional Neural Network for Edge Detection in Musculoskeletal Ultrasound Images.

Promise and Perils of Dynamic Sensitivity Control in IEEE 802.11ax WLANs (2016)
Presentation / Conference Contribution
Zhong, Z., Cao, F., Kulkarni, P., & Fan, Z. (2016, September). Promise and Perils of Dynamic Sensitivity Control in IEEE 802.11ax WLANs. Presented at 2016 13TH INTERNATIONAL SYMPOSIUM ON WIRELESS COMMUNICATION SYSTEMS (ISWCS, Poznan, Poland

Dynamic sensitivity control (DSC) is being discussed within the new IEEE 802.11ax task group as one of the potential techniques to improve the system performance for next generation Wi-Fi in high capacity and dense deployment environments, e.g. stadi... Read More about Promise and Perils of Dynamic Sensitivity Control in IEEE 802.11ax WLANs.

Diabetic macular edema grading based on deep neural networks (2016)
Presentation / Conference Contribution
Al-Bander, B., Al-Nuaimy, W., Al-Taee, M. A., Williams, B. M., & Zheng, Y. Diabetic macular edema grading based on deep neural networks. Presented at Ophthalmic Medical Image Analysis Third International Workshop, Athens, Greece

Diabetic Macular Edema (DME) is a major cause of vision loss in diabetes. Its early detection and treatment is therefore a vital task in management of diabetic retinopathy. In this paper, we propose a new featurelearning approach for grading the seve... Read More about Diabetic macular edema grading based on deep neural networks.

Detecting Similarities in Mobility Patterns (2016)
Presentation / Conference Contribution
Cottone, P., Ortolani, M., & Pergola, G. (2016, August). Detecting Similarities in Mobility Patterns. Presented at 8th European Starting AI Researcher Symposium (STAIRS 2016), The Hague, the Netherlands

The wide spread of low-cost personal devices equipped with GPS sensors has paved the way towards the creation of customized services based on user mobility habits and able to track and assist users in everyday activities, according to their current l... Read More about Detecting Similarities in Mobility Patterns.

Gaining insight by structural knowledge extraction (2016)
Presentation / Conference Contribution
Cottone, P., Gaglio, S., Lo Re, G., & Ortolani, M. (2016, August). Gaining insight by structural knowledge extraction. Presented at ECAI'16: Proceedings of the Twenty-second European Conference on Artificial Intelligence

The availability of increasingly larger and more complex datasets has boosted the demand for systems able to analyze them automatically. The design and implementation of effective systems requires coding knowledge about the application domain inside... Read More about Gaining insight by structural knowledge extraction.

An Efficient Consumption Optimisation for Dense Neighbourhood Area Demand Management (2016)
Presentation / Conference Contribution
Zhu, Z., & Fan, Z. (2016, April). An Efficient Consumption Optimisation for Dense Neighbourhood Area Demand Management. Presented at IEEE INTERNATIONAL ENERGY CONFERENCE (ENERGYCON)., Leuven, Belgium

Enabled by the information and communication technology (ICT), both system operators and consumers are able to make informed decisions on electricity demand management. Recent advances in theWide Area Measurement System (WAMS) provides better observa... Read More about An Efficient Consumption Optimisation for Dense Neighbourhood Area Demand Management.

Short term forecast of wind power generation based on SVM with pattern matching (2016)
Presentation / Conference Contribution
Zhu, Z., Zhou, D., & Fan, Z. (2016, April). Short term forecast of wind power generation based on SVM with pattern matching. Paper presented at 2016 IEEE INTERNATIONAL ENERGY CONFERENCE (ENERGYCON), Leuven, Belgium

This paper investigates short term forecast of wind power generation using Support Vector Machine (SVM) methods. We propose a similar pattern matching technique for data pre-processing. The proposed technique is able to select the most appropriate se... Read More about Short term forecast of wind power generation based on SVM with pattern matching.

From Uruk to Ur: Automated Matching of Virtual Tablet Fragments (2016)
Presentation / Conference Contribution
Gehlken, E., Collins, T., Woolley, S., Hanes, L., Lewis, A., Hernandez Munoz, L., & Ch’ng, E. (2016, July). From Uruk to Ur: Automated Matching of Virtual Tablet Fragments. Paper presented at 62nd Rencontre Assyriologique Internationale 2016, Ur in the Twenty-First Century CE, Philadelphia

Multimodal Multi-Stream Deep Learning for Egocentric Activity Recognition (2016)
Presentation / Conference Contribution
Song, S., Chandrasekhar, V., Mandal, B., Li, L., Lim, J.-H., Babu, G. S., San, P. P., & Cheung, N.-M. (2016, June). Multimodal Multi-Stream Deep Learning for Egocentric Activity Recognition. Presented at 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Las Vegas, NV, USA

In this paper, we propose a multimodal multi-stream deep learning framework to tackle the egocentric activity recognition problem, using both the video and sensor data. First, we experiment and extend a multi-stream Convolutional Neural Network to le... Read More about Multimodal Multi-Stream Deep Learning for Egocentric Activity Recognition.

Gl-learning: an optimized framework for grammatical inference (2016)
Presentation / Conference Contribution
Cottone, P., Ortolani, M., & Pergola, G. (2016, June). Gl-learning: an optimized framework for grammatical inference. Presented at CompSysTech '16: Computer Systems and Technologies 2016, Palermo Italy

In this paper, we present a new open-source software library, Gl-learning, for grammatical inference. The rise of new application scenarios in recent years has required optimized methods to address knowledge extraction from huge amounts of data and t... Read More about Gl-learning: an optimized framework for grammatical inference.

Virtual imaging for patient information on radiotherapy planning and delivery (2016)
Presentation / Conference Contribution
Sule-Suso, J., Finney, S., Bisson, J., Hammersley, S., Jassal, S., Knight, C., Ellis, C., Sargeant, S., Lam, K., Belcher, J., Collins, D., Bhana, R., Adab, F., O'Donovan, C., & Moloney, A. (2016, April). Virtual imaging for patient information on radiotherapy planning and delivery. Poster presented at ESTRO 35, Turin, Italy

Purpose or Objective: To assess whether both patients and
their relatives would welcome further information on a oneto-one basis on RT planning and delivery using the virtual
reality (VR) system VERT.

Monitoring Stem Cells in Phase Contrast Imaging (2016)
Presentation / Conference Contribution
Lam, K., Dempsey, K., Collins, D., & Richardson, J. Monitoring Stem Cells in Phase Contrast Imaging. Presented at SPIE BiOS 2016, San Francisco, California, United States

Understanding the mechanisms behind the proliferation of Mesenchymal Stem cells (MSCs) can offer a greater insight into the behaviour of these cells throughout their life cycles. Traditional methods of determining the rate of MSC differentiation rely... Read More about Monitoring Stem Cells in Phase Contrast Imaging.

#hayfever; A Longitudinal Study into Hay Fever Related Tweets in the UK (2016)
Presentation / Conference Contribution
de Quincey, E., Kyriacou, T., & Pantin, T. (2016, April). #hayfever; A Longitudinal Study into Hay Fever Related Tweets in the UK. Presented at 6th International Conference on Digital Health, Montreal

This paper describes a longitudinal study that has collected and analysed over 512,000 UK geolocated tweets over 2 years from June 2012 that contained instances of the words "hayfever" and "hay fever". The results indicate that the temporal distribut... Read More about #hayfever; A Longitudinal Study into Hay Fever Related Tweets in the UK.

WLAN Throughput Management: A Game Theoretic TXOP Scheduling Approach (2016)
Presentation / Conference Contribution
Zhu, Z., Cao, F., & Fan, Z. (2015, September). WLAN Throughput Management: A Game Theoretic TXOP Scheduling Approach. Presented at 2015 IEEE 20th International Workshop on Computer Aided Modelling and Design of Communication Links and Networks (CAMAD), Guildford, UK

This paper investigates the dynamic selection of transmission opportunity (TXOP) which was originally proposed in IEEE 802.11e Enhanced Distributed Channel Access (EDCA). A game theoretic optimisation framework is proposed to schedule the optimal TXO... Read More about WLAN Throughput Management: A Game Theoretic TXOP Scheduling Approach.