Browsing Department of Information and Communication Technology by Subject "Deep learning"

Browsing Department of Information and Communication Technology by Subject "Deep learning"

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  • 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) 
    Sankeetha, V.; 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 ...
  • 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 ...
  • 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, ...
  • 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 ...
  • Part of speech tagging for Tamil language using deep learning 
    Visuwalingam, H.; Sakuntharaj, R.; Ragel, R.G. (IEEE, 2021-12-09)
    Part of Speech (POS) tagging is the process of marking up a word in a sentence to a corresponding part of speech. POS tagging is considered one of the pre-processing steps in Natural Language Processing (NLP) applications ...
  • Sri Lankan seagrass families identification using underwater images through image enhancement and deep learning techniques 
    Diluxshan, J.; Athiththan, V.; Tuvensha, J.; 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 ...
  • Two's Complement: Monitoring Software Control Flow Using Both Power and Electromagnetic Side Channels 
    Amar, M.; Lojenaa, N.; Sayakkara, A.; Oren, Y. (IEEE, 2024-11-06)
    Embedded devices leak information about their inner activity through power and EM side channels. A defender who measures this leakage can thus use it to monitor the device and ensure its control-flow integrity. Previous ...

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