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Browsing by Subject "machine learning"

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Chronic Kidney Disease Prediction Using Machine Learning Methods

Ekanayake, IU; Herath, D [Conference-Full-text]

Chronic Kidney Disease (CKD) or chronic renal disease has become a major issue with a steady growth rate. A person can only survive without kidneys for an average time of 18 days, which makes a huge demand for a kidney ...
Classification of cyberbullying Sinhala language comments on social media

Amali, HMAI; Jayalal, S; Jayalal, S [Conference-Full-text]

Due to technological revolution over the years, bullying which was confined to physical boundaries has now moved online. Denigration or insult is one form of cyberbullying. According to Sri Lanka Computer Emergency Readiness ...
Detection of novel biomarker genes of alzheimer’s disease using gene expression data

Perera, S; Hewage, K; Gunarathne, C; Navarathna, R; Herath, D; Ragel, RG [Conference-Full-text]

It is well recognized, that most common form of dementia is Alzheimer’s disease and a successful cure or medication is not discovered. A plethora of research has been conducted to understand the underlying mechanism and ...
Forest sound classification dataset: FSC22

Bandara, M; Jayasundara, R; Ariyarathne, I; Meedeniya, D; Perera, C [Article-Full-text]

The study of environmental sound classification (ESC) has become popular over the years due to the intricate nature of environmental sounds and the evolution of deep learning (DL) techniques. Forest ESC is one use case of ...
Highly sensitive quantitative phase microscopy and deep learning aided with whole genome sequencing for rapid detection of infection and antimicrobial resistance

Ahmad, A; Hettiarachchi, R; Khezri, A; Ahluwalia, BS; Wadduwage, DN; Ahmad, R [Article-Full-text]

Current state-of-the-art infection and antimicrobial resistance (AMR) diagnostics are based on culture-based methods with a detection time of 48-96 h. Therefore, it is essential to develop novel methods that can do real-time ...
A hybrid ontology-based information extraction system

Gutierrez, F; Dou, D; Fickas, S; Wimalasuriya, D; Zong, H [Article-Full-text]

Information Extraction is the process of automatically obtaining knowledge from plain text. Because of the ambiguity of written natural language, Information Extraction is a difficult task. Ontology-based Information ...
Machine learning approach to recognize subject based sentiment values of reviews

De Mel, NM; Hettiarachchi, HH; Madusanka, WPD; Malaka, GL; Perera, AS; Kohomban, U [Conference-Full-text]

Due to the increase in the number of people participating online on reviewing travel related entities such as hotels, cities and attractions, there is a rich corpus of textual information available online. However, to ...
Neural network approach to classify defect types in cotton yarns

Amarathunga, S; Vidushka, K; Niles, SN; Abesooriya, RP [Conference-Extended-Abstract]

Accurate identification and classification of defects in cotton yarns are crucial for ensuring the quality and consistency of textile products. Defects can lead to compromised fabric quality, reduced durability, and increased ...
Reducing computational time of closed-loop weather monitoring: a complex event processing and machine learning based approach

Chandrathilake, HMC; Hewawitharana, HTS; Jayawardana, RS; Viduranga, ADD; Bandara, HMND; Marru, S; Perera, S [Conference-Full-text]

Modern weather forecasting models are developed to maximize the accuracy of forecasts by running computationally intensive algorithms with vast volumes of data. Consequently, algorithms take a long time to execute, and ...
ReputationBox: A system to analyse importance of emails and reputation of email senders

Jayakody, D; Dias, G [Conference-Abstract]

E-mail is one of the primary mediums of electronic communication used today. The number of email accounts are expected to go over 4.3 billion accounts by the year 2016 according to the latest email statistic reports. Users ...
Sensing eating events in context: A smartphone-only approach

Bangamuarachch, W; Chamantha, A; Meegahapola, L; Ruiz-Correa, S; Perera, I; Gatica-Perez, D [Article-Full-text]

While the task of automatically detecting eating events has been examined in prior work using various wearable devices, the use of smartphones as standalone devices to infer eating events remains an open issue. This paper ...

Browsing by Subject "machine learning"

Browsing by Subject "machine learning"

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