Outputs (291)

Comparison of Sentiment Analysis Approaches Using Modern Arabic and Sudanese Dialect (2018)
Conference Proceeding
Hussien, I., Dashtipour, K., & Hussain, A. (2018). Comparison of Sentiment Analysis Approaches Using Modern Arabic and Sudanese Dialect. In Advances in Brain Inspired Cognitive Systems (615-624). https://doi.org/10.1007/978-3-030-00563-4_60

Sentiment analysis mainly focused on the automatic recognition of opinions’ polarity, as positive or negative. Nowadays, sentiment analysis is replacing the web-based and traditional survey methods commonly conducted by companies for finding the publ... Read More about Comparison of Sentiment Analysis Approaches Using Modern Arabic and Sudanese Dialect.

A Semi-supervised Corpus Annotation for Saudi Sentiment Analysis Using Twitter (2018)
Journal Article
Alqarafi, A., Adeel, A., Hawalah, A., Swingler, K., & Hussain, A. (2018). A Semi-supervised Corpus Annotation for Saudi Sentiment Analysis Using Twitter. Lecture Notes in Computer Science, 589-596. https://doi.org/10.1007/978-3-030-00563-4_57

In the literature, limited work has been conducted to develop sentiment resources for Saudi dialect. The lack of resources such as dialectical lexicons and corpora are some of the major bottlenecks to the successful development of Arabic sentiment an... Read More about A Semi-supervised Corpus Annotation for Saudi Sentiment Analysis Using Twitter.

A Novel Semi-supervised Classification Method Based on Class Certainty of Samples (2018)
Conference Proceeding
Gao, F., Yue, Z., Xiong, Q., Wang, J., Yang, E., & Hussain, A. (2018). A Novel Semi-supervised Classification Method Based on Class Certainty of Samples. . https://doi.org/10.1007/978-3-030-00563-4_30

The traditional classification method based on supervised learning classifies remote sensing (RS) images by using sufficient labelled samples. However, the number of labelled samples is limited due to the expensive and time-consuming collection. To e... Read More about A Novel Semi-supervised Classification Method Based on Class Certainty of Samples.

A Convolutional Neural Network approach for classification of dementia stages based on 2D-spectral representation of EEG recordings (2018)
Journal Article
Ieracitano, C., Mammone, N., Bramanti, A., Hussain, A., & Morabito, F. (2019). A Convolutional Neural Network approach for classification of dementia stages based on 2D-spectral representation of EEG recordings. Neurocomputing, 323, 96-107. https://doi.org/10.1016/j.neucom.2018.09.071

A data-driven machine deep learning approach is proposed for differentiating subjects with Alzheimer’s Disease (AD), Mild Cognitive Impairment (MCI) and Healthy Control (HC), by only analyzing noninvasive scalp EEG recordings. The methodology here pr... Read More about A Convolutional Neural Network approach for classification of dementia stages based on 2D-spectral representation of EEG recordings.

Biomimetic pupils for augmenting eye emulation in humanoid robots (2018)
Journal Article
Strathearn, C., & Ma, M. (2018). Biomimetic pupils for augmenting eye emulation in humanoid robots. Artificial Life and Robotics, 23(4), 540-546. https://doi.org/10.1007/s10015-018-0482-6

Contemporary approaches in the development of humanoid robots continually neglect holistic nuances, particularly in ocular prosthetic design. The standard solid glass and acrylic eye construction techniques implemented in humanoid robot design presen... Read More about Biomimetic pupils for augmenting eye emulation in humanoid robots.

Root Gap Correction with a Deep Inpainting Model (2018)
Conference Proceeding
Chen, H., Giuffrida, M. V., Doerner, P., & Tsaftaris, S. A. (2018). Root Gap Correction with a Deep Inpainting Model.

Imaging roots of growing plants in a non-invasive and affordable fashion has been a long-standing problem in image-assisted plant breeding and phenotyping. One of the most affordable and diffuse approaches is the use of mesocosms, where plants are gr... Read More about Root Gap Correction with a Deep Inpainting Model.

DNA Sequence Based Medical Image Encryption Scheme (2018)
Conference Proceeding
Khan, J. S., Ahmad, J., Abbasi, S. F., Ali, A., & Kayhan, S. K. (2018). DNA Sequence Based Medical Image Encryption Scheme. In 2018 10th Computer Science and Electronic Engineering (CEEC). https://doi.org/10.1109/ceec.2018.8674221

Medical consultants and doctors store and update patients confidential information on Internet cloud computing platforms. These days, securing medical images from eavesdroppers is one of the most challenging and significant research areas. Due to var... Read More about DNA Sequence Based Medical Image Encryption Scheme.

A Novel Random Neural Network Based Approach for Intrusion Detection Systems (2018)
Conference Proceeding
Qureshi, A., Larijani, H., Ahmad, J., & Mtetwa, N. (2018). A Novel Random Neural Network Based Approach for Intrusion Detection Systems. . https://doi.org/10.1109/ceec.2018.8674228

Computer security and privacy of user specific data is a prime concern in day to day communication. The mass use of internet connected systems has given rise to many vulnerabilities which includes attacks on smart devices. Regular occurrence of such... Read More about A Novel Random Neural Network Based Approach for Intrusion Detection Systems.

Collaborative Computing: Networking, Applications and Worksharing: 13th International Conference, CollaborateCom 2017, Edinburgh, UK, December 11–13, 2017, Proceedings (2018)
Conference Proceeding
(2018). Collaborative Computing: Networking, Applications and Worksharing: 13th International Conference, CollaborateCom 2017, Edinburgh, UK, December 11–13, 2017, Proceedings. In I. Romdhani, L. Shu, H. Takahiro, Z. Zhou, T. Gordon, & D. Zeng (Eds.), Collaborative Computing: Networking, Applications and Worksharing. https://doi.org/10.1007/978-3-030-00916-8

This book constitutes the thoroughly refereed proceedings of the 13th International Conference on Collaborative Computing: Networking, Applications, and Worksharing, CollaborateCom 2017, held in Edinburgh, UK, in December 2017. The 65 papers presente... Read More about Collaborative Computing: Networking, Applications and Worksharing: 13th International Conference, CollaborateCom 2017, Edinburgh, UK, December 11–13, 2017, Proceedings.

Monitoring Home Energy Usage Using an Unsupervised NILM Algorithm Based on Entropy Index Constraints Competitive Agglomeration (EICCA) (2018)
Conference Proceeding
Kamoto, K. M., & Liu, Q. (2018). Monitoring Home Energy Usage Using an Unsupervised NILM Algorithm Based on Entropy Index Constraints Competitive Agglomeration (EICCA). . https://doi.org/10.1007/978-3-030-00018-9_42

Given that residential sectors in both developed and developing nations contribute to a significant portion of electric energy consumption, addressing energy efficiency and conservation in this sector is envisioned to have a considerable effect on th... Read More about Monitoring Home Energy Usage Using an Unsupervised NILM Algorithm Based on Entropy Index Constraints Competitive Agglomeration (EICCA).