Research Publications Authored by SLIIT Staff

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This collection includes all SLIIT staff publications presented at external conferences and published in external journals. The materials are organized by faculty to facilitate easy retrieval.

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Author: search.filters.author.Perera, YHas files: Yes

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    LISA : Enhance the explainability of medical images unifying current XAI techniques
    (IEEE, 2022-07-18) Abeyagunasekera, S. H. P; Perera, Y; Chamara, K; Kaushalya, U; Sumathipala, P
    This work proposed a unified approach to increase the explainability of the predictions made by Convolution Neural Networks (CNNs) on medical images using currently available Explainable Artificial Intelligent (XAI) techniques. This method in-cooperates multiple techniques such as LISA aka Local Interpretable Model Agnostic Explanations (LIME), integrated gradients, Anchors and Shapley Additive Explanations (SHAP) which is Shapley values-based approach to provide explanations for the predictions provided by Blackbox models. This unified method increases the confidence in the black-box model’s decision to be employed in crucial applications under the supervision of human specialists. In this work, a Chest X-ray (CXR) classification model for identifying Covid-19 patients is trained using transfer learning to illustrate the applicability of XAI techniques and the unified method (LISA) to explain model predictions. To derive predictions, an image-net based Inception V2 model is utilized as the transfer learning model.
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    Intelligent mobile assistant for hearing impairers to interact with the society in Sinhala language
    (IEEE, 2017-12-06) Perera, Y; Jayalath, N; Tissera, S; Bandara, o; Thelijjagoda, S
    A language is a way of words or signs that people use to share feelings and ideas with each other. In view of the society there is an issue in communication among hearing impaired people and hearing people. Most of the hearing people have no idea about the sign languages and they are not having any desire to learn sign language. Thus, typically hearing impairers are used to be isolated. When considering about all the solutions there is an absence of a Sinhala application with Sinhala sign language. Sinhala is the native language of the Sinhalese people. Sinhala is one of the official and national languages of Sri Lanka, who make up the largest ethnic group in Sri Lanka, numbering about 20 million. Sinhalese is also spoken as a second language by other ethnic groups in Sri Lanka, totaling about four million. Since most of the solutions are desktop applications, hearing impairers feel so uncomfortable. In the modern era where mobile technology plays a superior role in day to day life, Project “Sanwadha” is an intelligent assistant for the hearing-impaired people for communication. The proposed application is under cross platform mobile development where users can reach the solution widely. The core of the Project “Sanwadha” is Instant Messaging (IM) chat. Here the application will get the text from the ordinary person in Sinhala language and it converts to Sinhala sign language. The message will be directing to hearing impaired person in a format of GIF. 2D model can be used by the User (Hearing impaired) to grasp the idea by creating the sign as they wish. That sign would be altering in to either Text or Voice to interact with the society. Hearing people also can cooperate with the hearing impairers with the voice recognition mechanism. This solution would come up with an intelligent application where hearing impairers makes empower in the society through communication. Reaching Sri Lankan deaf community is another foremost objective of this project. This hopes to narrow digital divide that between enabled and hearing- impaired users. The significance of this proposed application is that it allows hearing-impaired individuals to communicate when they are long distance apart. This application would bridge the gap between hearing impairers with the society.