Browsing by Author "De Silva, H."

Now showing 1 - 5 of 5

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Deep Transfer Learning Approach for Facial and Verbal Disease Detection
(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Manage, D.M.; Alahakoon, A.M.I.S.; Weerathunga, K.; Weeratunga, T.; Lunugalage, D.; De Silva, H.
Millions of people have been subjected to different kind of acute diseases, some of them are eye diseases, facial skin diseases, tongue diseases and voice abnormalities. Most of eye diseases cause fully or partial blindness. Skin and tongue complications can be signs of cancers. Voice abnormalities can be cured at initial stages. Well-practiced medical practitioners have the ability of diagnose these diseases, but due to the pandemic situations and high consultation costs people do not tend to consult doctors. This research is predominantly focused on development of an application for automatic detection of eye, skin, tongue and verbal diseases using transfer learning (TL) based deep learning (DL) approach. Deep learning is a part of machine learning (ML) which has been used in most computer vision approaches. Transfer learning has been used to rebuild the existing convolutional neural network (CNN) models and used in disease detection. DenseNet121, MobileNetV2, RestNet152V2, models have been used to detect eye, skin and tongue diseases respectively and a new model has been used to detect voice abnormalities. CNN models are capable of automatically extracting features from the given images and voice data. All the trained models have been given accuracy rate of 80%-95%.
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Innovative, Integrated and Interactive (3I) LMS for Learners and Trainers
(2020 2nd International Conference on Advancements in Computing (ICAC), SLIIT, 2020-12-10) Fernando, K.J.L.; Jayalath, W.J.D.L.D.D.; Ranasinghe, A.D.R.N.; Bandara, P.K.B.P.S.; De Silva, H.
3I-LMS is meant to conquer the insurmountable restraints to class/lecture room education. What are insurmountable restraints to physical classroom education and how does 3I-LMS conquer them. Firstly, the lockdown and physical distancing warranted by the spread of Covid-19. In order to overcome the restraints of the pandemic 3I-LMS would be the obvious answer. 3I-LMS, the medium for delivery and reception, is online for both learners and trainers. Secondly, ineffectiveness resulting in frail in pass rates, fast diminishing memory, faulty study techniques are overcome. 3I-LMS makes studying satisfied, gamified, engaged and enjoying. The outcome would be lasting memory, effective study techniques, higher recall rates leading to improved pass rates. Thirdly, inefficiencies such as slow access to relevant lessons, notes, slow answer evaluation, feedback, clarification to routine questions are also resolved by 3I-LMS. 3I-LMS provides for keyword search, relevant subject wise notes, instant answers for routine questions thus contributing to improved efficiencies. Additionally, 3I-LMS has unique and innovative features to assist assignment completion, emanate milestone alerts, monitoring emotions and time utilization. 3I-LMS provides for utmost security. Thus, the solution deploys face recognition and keystroke dynamics to combat impersonation, copying and unauthorized referencing.
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Machine Learning-Based Smart Shopping for Visually Impaired
(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Nagenthiran, N.; Priyanha, P.; Nirosha, S.; Vivek, J.; De Silva, H.; Sriyaratna, D.
There are diverse applications built for the e- commerce platform, each with its own set of advantages. All goods should be relevant to all members of society around the world, but there are people with unique needs who should be considered when technology advancements are made for the common good. People who are blind require particular attention since they require assistance from others. For this research, we referred to several studies with comparable goals and approaches, which our group closely examined to enhance our study and outcomes, and which were highlighted when relevant work was discussed. The purpose of this study is to provide accessibility for all members of society, including the blind, as well as location-based solutions for consumers. These include voice navigation through the app, product suggestions, offering quick paths to the shop location by comparing existing algorithms for identifying short paths and providing a function to give voice feedback. This paper thoroughly examined the findings and provided appropriate evidence to support the answer to the challenge mentioned above. This sort of research will have a beneficial influence on our IT companies' consideration for those who live with specific needs that technology may help them meet.
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Machine Learning-Based Smart Shopping for Visually Impaired
(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Nagenthiran., N.; Priyanha, P.; Nirosha, S.; Vivek., J.; De Silva, H.; Sriyaratna, D.
There are diverse applications built for the e- commerce platform, each with its own set of advantages. All goods should be relevant to all members of society around the world, but there are people with unique needs who should be considered when technology advancements are made for the common good. People who are blind require particular attention since they require assistance from others. For this research, we referred to several studies with comparable goals and approaches, which our group closely examined to enhance our study and outcomes, and which were highlighted when relevant work was discussed. The purpose of this study is to provide accessibility for all members of society, including the blind, as well as location-based solutions for consumers. These include voice navigation through the app, product suggestions, offering quick paths to the shop location by comparing existing algorithms for identifying short paths and providing a function to give voice feedback. This paper thoroughly examined the findings and provided appropriate evidence to support the answer to the challenge mentioned above. This sort of research will have a beneficial influence on our IT companies' consideration for those who live with specific needs that technology may help them meet.
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PatientCare: Patient Assistive Tool with Automatic Hand-written Prescription Reader
(2020 2nd International Conference on Advancements in Computing (ICAC), SLIIT, 2020-12-10) Kulathunga, D.; Muthukumarana, C.; Pasan, U.; Hemachandra, C.; Tissera, M.; De Silva, H.
Most people in the world prefer to be conscious of the medications prescribed by physicians. Especially, the importance of handwritten prescriptions is prodigious in Sri Lanka because they are widely used in the healthcare sector. However, due to the illegible handwriting and the medical abbreviations of the physicians, patients are unable to find the prescribed medication information. This research is an attempt to assist the patients in identifying the prescribed medicine information and minimizes misreading errors of medical prescriptions. When a patient uploads the image of a prescription, the system converts it into unstructured text data by using OCR and segmentation, then NER is used to categorize medical information from given text. According to the other research, some solutions exist in other domains for the above mechanisms. But they gave less accuracy when tried to apply for this research due to the domain specialty. Therefore, as a solution to overcome the above discrepancy this approach allows users to scan handwritten medical prescriptions and blood reports and obtain analyzed reports in medical history. Results have shown that this approach will give 64%-70% accuracy level in doctor's handwriting recognition and 95%- 98% accuracy in medical information categorization of the prescription format.