• Predictive Tool to Overcome Negative Thinking of Employees with Anxiety 

  Ananda, Kalana Gayantha; Ratnayake, Gayashini Shyanka (IEEE, 2022)

  Among significant portion of the population, anxiety disorder can be considered as the most prominent psychological condition. Anxiety may limit many people's activities and make it difficult for them to enjoy their lives. ...
• Evol-AutoNN: Evolutionary Automation of Neural Network 

  Sivapathasundaram, Janakan; Poravi, Guhanathan (IEEE, 2022)

  As the domain of data science keeps on growing it leads to the need for a tool that breaks the barriers for non-experts to get into the field of data science. In this paper, we introduce the project of automating the neural ...
• A Systematic Literature Review of Machine Learning based Approaches on Pathology Detection in Gastrointestinal Endoscopy 

  Gunaratna, Dinisuru Nisal; Fernando, Pumudu (IEEE, 2022)

  Endoscopy is the most widely adhered medical procedure used to examine the gastrointestinal tract of a person. Accurate pathology detection during the endoscopic procedure is crucial as misidentifications or miss rates ...
• A Visually Interpretable Forensic Deepfake Detection Tool Using Anchors 

  Jayakumar, Krishnakripa (IEEE, 2022)

  “Deepfakes” have seen a dramatic rise in recent times and are becoming quite realistic and indistinguishable with the advancement of deepfake generation techniques. Promising strides have been made in the deepfake detection ...
• Predictive Tool for Peer Support and Mental Health Improvement with Speech Emotion State Classification for University Students 

  Welaratne, Hasitha Chamod; Ratnayake, Gayashini Shyanka (IEEE, 2022)

  Mental health issues such as stress, depression, anxiety and trauma are some of the most common disorders which is mainly affecting many university student’s academics and their future careers. These mental health conditions ...
• An Analysis of the Features Considerable for NFT Recommendations 

  Piyadigama, Dinuka; Poravi, Guhanathan (IEEE, 2022)

  This research explores the methods that Non-fungible Token (NFT)s can be recommended to people who inter-act with NFT-marketplaces to explore NFTs of preference and similarity to what they have been searching for. While ...
• Pulsar Candidate Selection Using Gaussian Hellinger Extremely Fast Decision Tree 

  Gamage, Venoli; Ayoob, Mohamed; Jayakumar, Krishnakripa (IEEE, 2022)

  Radio wave data gathered by pulsar finding telescopes are required to be classified while being streamed. The reason for that is the practical constraints of traditional machine learning algorithms on streaming datasets. ...
• A Review On Breaking the Limits of Time Series Forecasting Algorithms 

  Raneez, Ammar; Wirasingha, Torin (IEEE, 2023)

  Time Series (TS) forecasting has stagnated owing to algorithm restrictions, therefore systems developed using these methods can only perform so well. TS remains a challenge despite recent advances in Deep Learning (DL) in ...
• Towards True Decentralization: Development, Testing and Evaluation of a Novel Blockchain Consensus Protocol 

  Wimal, Kesara; Liyanage, Geethapriya (Springer Link, 2023)

  The blockchain technology that powers the Bitcoin network was unveiled to the world in 2008. After more than a decade of research and development, a number of blockchain systems have been put out by both industry and ...
• AutoNLP: A Framework for Automated Model Selection in Natural Language Processing 

  Saleem, Shehan; Kumarapathirage, Sapna (IEEE, 2023)

  Although numerous open-source tools exist for machine learning with tabular data, there is a scarcity of comparable resources tailored specifically for NLP. The lack of transparency in the inner workings of existing AutoNLP ...
• A Machine Learning-Based Job Forecasting And Trend Analysis System To Predict Future Job Markets Using Historical Data 

  Senthurvelautham, Sharanaja; Senanayake, Nipuna (IEEE, 2023)

  Over the last two decades, technological advancements have created more job markets and job opportunities than ever. With the ever-increasing demand, it has become vital for academic institutions and businesses to keep up ...
• An Ontological Approach for Understanding Animal Diseases and Their Symptoms 

  Bandara, Viraj Lakshitha; Yapa, Prasan (2023)

  The accurate and timely diagnosis of animal diseases is essential for the health and well-being of animals, as well as for the prevention and control of disease outbreaks. One important aspect of disease diagnosis is the ...
• Deep Learning Based Framework for Reliable Sri Lankan Currency Authentication and Counterfeit Prevention 

  Abhishek, Yohan; Nadeem, Nishaam; Delankawala, Sayumi; Jayakody, Senesh; Sumanathilaka, T.G.D.K. (IEEE, 2023)

  Digital image processing plays a crucial role in enabling efficient and precise analysis, manipulation, and enhancement of images. In this study, researchers address challenges faced by individuals with visual impairments ...
• Neural Architecture Search for Generative Adversarial Networks: A Review 

  Buthgamumudalige, Vinula Uthsara; Wirasingha, Torin (IEEE, 2021)

  Achieving competent image generation results in Generative Adversarial Networks (GANs) has been observed to be weighed down by barriers such as mode collapse and being error-prone, due to the time consumption, effort and ...
• Optimized Duplicate Question Detection in Programming Community Q&A Platforms using Semantic Hashing 

  Koswatte, Dehami Deshan; Hettiarachchi, Saman (IEEE, 2021)

  Duplicate Question Detection (DQD) in Programming Community Question & Answer (PCQA) platforms has been a highly prominent area of research in the recent past. A lot of studies use Semantic Text Similarity (STS) as a key ...
• AdaptText: A Novel Framework for Domain-Independent Automated Sinhala Text Classification 

  Kodithuwakku, Yathindra; Hettiarachchi, Saman (IEEE, 2021)

  Sinhala language is being the widely used language in Sri Lanka. With the advancement of internet usage in Sri Lanka, an incredible amount of Sinhala text data is being added to the internet. In order to manage, analyze ...
• Impact on JPEG Image Steganalysis using Transfer Learning 

  Padmasiri, Avishka Thushan; Hettiarachchi, Saman (IEEE, 2021)

  Image steganography is a convenient candidate for information hiding with the upsurge of using images on social media platforms and the internet. It is equally important that detecting these images through steganalysis so ...
• An Analysis of Face Recognition under Face Mask Occlusions 

  Hemathilaka, S; Aponso, A (Academy and Industry Research Collaboration Center (AIRCC), 2021)

  The face mask is an essential sanitaryware in daily lives growing during the pandemic period and is a big threat to current face recognition systems. The masks destroy a lot of details in a large area of face and it makes ...
• Automating Generative Adversarial Networks using Neural Architecture Search: A Review 

  Ganepola, V V V; Wirasingha, T (2021)

  Semantic image segmentation is a crucial task in various fields that use computer-vision based applications. Generative Adversarial Networks (GANs) are attracting widespread interest in the data science community for their ...
• DERAINIZER for Unpaired Single Image De-raining 

  Fernando, H; Ayoob, M; Poravi, Guhanathan (IEEE, 2021)

  Rain streaks are known to cause many performance or accuracy reductions in many computer vision systems. The problem of obstructing rain streaks is addressed within the domain of “De-raining”. De-raining is the process of ...

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