• Classification of Sri Lankan Skin Diseases Using Ensemble Deep Learning Models 

  Thapalingasivam, K.; Vinoharan, V.; Sivanesan, P. (IEEE, 2024)

  Skin disease detection is a critical component of dermatological healthcare, traditionally dependent on dermatologists’ expertise for accurate diagnosis. However, manual diagnosis can be time-consuming and prone to errors, ...
• Deep-Machine Learning Integration for Enhanced Pest Detection in Mangifera indica (Mango) 

  Vamadevan, S.; Vinoharan, A.; Vinoharan, V. (IEEE, 2026)

  Mango (Mangifera indica), the third most widely consumed fruit in Sri Lanka after banana and papaya, has experienced steady growth in cultivation and yield; however, pest and disease infestations still cause substantial ...
• Machine Learning for Effective Pest Detection in Mangifera indica (Mango) Crop Protection 

  Vamadevan, S.; Vinoharan, A.; Vinoharan, V. (IEEE, 2025)

  Mangifera indica, a key fruit crop in Sri Lanka, supports both agriculture and rural livelihoods but suffers significant losses from pest infestations. Early pest detection is crucial to reduce damage, yet manual inspection ...
• Adapting Prompt-Driven Approach for Diabetic Foot Ulcer Segmentation: A Sri Lankan Patient Study 

  Herath, W. R. G. A. D. P.; Vinoharan, V.; Kumaralingam, L.; Nagulan, R.; Bramya, S. (IEEE, 2024)

  Diabetes, a widespread metabolic disorder affecting millions globally, including many in Sri Lanka, often results in diabetic foot ulcers (DFUs). Accurate wound measurement is vital for diagnosing and monitoring DFUs, ...
• Sinhala-English Code-Mixed Corpus for Sentiment Analysis: Development and Baseline Evaluation 

  Perera, W.A.S.C.; Caldera, H.A. (IEEE, 2026)

  Language mixing and informal usage in code-mixed text make sentiment analysis a challenging task. Although a large number of linguistic resources are available for monolingual languages, lexicon and dataset resources are ...
• An Efficient Hybrid Model for Early Detection of Mango Leaf Pests 

  Sankeetha, V.; Agalya, V.; Vinoharan, V. (CSC-University of Jaffna, 2025)

  Mango is a vital cash crop widely cultivated across tropical and subtropical regions, including Sri Lanka, where it contributes significantly to agricultural income and rural livelihoods. However, mango cultivation is often ...
• Assessing Integration of Environmental Literacy Competencies in Sri Lankan Junior Secondary Science Syllabi: A Quantitative Content Analysis 

  Agalya, V.; Vinoharan, V. (Ministry of education, 2024)

  Sri Lanka, despite its extensive history of environmental policy and legislation, experiences significant environmental challenges as a developing nation due to rapid urbanization and population concentration in urban ...
• A Content Analysis of Textbook: Investigating the Environmental Literacy Skill in Sri Lankan Grade 6 Science Textbooks 

  Agalya, V.; Vinoharan, V. (Trincomalee Campus - Eastern University Sri Lanka, 2024)

  In Sri Lankan general education, textbooks play a pivotal role in the teaching-learning process. Grade 6 marks the commencement of science education as a distinct subject, introducing students to fundamental scientific ...
• Environmental Literacy of Junior Secondary Students in Sri Lanka 

  Vinoharan, A.; Vinoharan, V. (SLIIT, 2024)

  Human development without considering the impact on the environment has created numerous global issues, prompting policymakers to prioritise environmental protection. As environmental issues became pressing concerns, the ...
• Impact of Bilingual Education on General Certificate of Education (GCE), ordinary Level (O/L) English Results, Sri Lanka 

  Vinoharan, A.; Vinoharan, V. (University of Jaffna, 2024)

  Sri Lanka, despite its relatively high literacy rate compared to other South Asian nations, faces challenges in developing a workforce proficient in English, aligning with labor market demands. To address this, Bilingual ...
• Assessing Environmental Literacy Integration and Student Proficiency in Grade 9 Science Curriculum 

  Agalya, V.; Vinoharan, V. (Faculty of Education University of Colombo, 2024)

  Sri Lankan policymakers prioritize sustainable development through biodiversity conservation and the creation of clean residential environments. The development of environmental literacy (EL) skills among citizens is ...
• Fake News Detection Using Machine Learning 

  Edirisinghe, E.M.M.W.; Vinoharan, V. (Dept. of Computer Science, University of Jaffna, 2023)

  The spreading of fake news via diverse media is a major issue due to its potential to cause significant harmful impacts on society. Although social media is an emerging field offering various benefits, the reliability ...
• Common technique for detecting and correcting both non-word and real-word errors in Tamil sentences 

  Sakuntharaj, R.; Mahesan, S. (7th Ruhuna International Science & Technology Conference, 2020)

  Erroneous words can be classified into two categories, namely non-word errors and real-word errors. These errors can occur in sentences when typing a document due to fast typing, switching of fingers on keys, input tools ...
• Do images really do the talking? analysing the significance of images in tamil troll meme classification 

  Hegde, S. U.; Hande, A.; Priyadharshini, R.; Thavareesan, S.; Sakuntharaj, R.; Thangasamy, S.; Bharathi, B.; Chakravarthi, B. (Advances in Computational Intelligence, 2025)

  A meme is a part of media created to share an opinion or emotion across the internet. Due to their popularity, memes have become the new form of communication on social media. However, they are used in harmful ways such ...
• Extraction of Sentiments in Tamil Sentences Using Deep Learning 

  Loganathan, H.; Sakuntharaj, R. (2022 International Research Conference on Smart Computing and Systems Engineering (SCSE), 2022)

  Sentiment analysis is the process of extracting information from the given text in which the text consists of various sensations such as happiness, perturbation, pride, worry, and so on about various functions, human beings, ...
• A Sequential DNN for Sentiment Analysis of Dravidian Code-Mixed Language Comments on YouTube 

  Aaron Samuel, A.; Sambath Kumar, L.; Navaneethakrishnan, S.; Sakuntharaj, R. (FIRE 2022 - Forum for Information Retrieval Evaluation, December 9-13, 2022, Kolkata, India, 2022)

  A method for determining if a block of text is positive, neutral, or negative is sentiment analysis. As code-mixed material in many native languages is becoming increasingly widespread, there is also an increasing need for ...
• Sri Lankan seagrass families identification using underwater images through image enhancement and deep learning techniques 

  Diluxshan, J.; Athiththan, V.; Jegatheeswaran, T.; Keerthanaram, T.; Jeyamugan, T.; Nagulan, R. (ICITR, University of Moratuwa, Sri Lanka, 2025)

  Seagrass ecosystems play a vital role in marine biodiversity, carbon sequestration, and coastal protection, yet their monitoring is limited by challenges in underwater imaging and manual species identification. Automated ...
• Deep Learning for Intelligent Waste Sorting in Sri Lanka: A Conceptual Review 

  Herath, H.M.P.H.S.; Kuruneru, R.P.D.; Logeesan, R.; Venuja, N. (Faculty of Technological Studies, University of Vavuniya, 2025)

  Urban waste management in Sri Lanka is increasingly challenged by rising waste volumes, reliance on manual sorting, and inefficient collection systems. This review paper aims to examine how deep learning, particularly ...
• Sense Step: An Innovative Smart Cane for Visually Impaired Individuals 

  Tharsayani, M.; Thisakaran, R. (Faculty of Technological Studies, University of Vavuniya, 2025)

  Sense Step is an innovative smart cane designed to empower visually impaired individuals through advanced assistive technology. Traditional mobility aids lack critical features to ensure user safety and independence, leaving ...
• Harvest Guardian: A Mobile Toolkit for AI-Based Crop Disease Diagnosis and Farmer Decision Support 

  Thivakaran, V.; Thisakaran, R. (Faculty of Technological Studies, University of Vavuniya, 2025)

  Agriculture in Sri Lanka is predominantly driven by smallholder farmers who face challenges in timely disease detection, access to localized expert advice, and planning around weather conditions. These issues contribute ...

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