Lily Dey

ORCID: 0009-0003-5855-6693
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About
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Research Areas
  • Advanced Text Analysis Techniques
  • Sentiment Analysis and Opinion Mining
  • Ethics and Social Impacts of AI
  • Explainable Artificial Intelligence (XAI)
  • AI in cancer detection
  • Multi-Criteria Decision Making
  • Brain Tumor Detection and Classification
  • Anomaly Detection Techniques and Applications
  • Human-Automation Interaction and Safety
  • Artificial Intelligence in Healthcare and Education
  • Spam and Phishing Detection
  • Sports injuries and prevention
  • Emotion and Mood Recognition
  • Text and Document Classification Technologies
  • Sports Analytics and Performance

University of Calgary
2024

University of Chittagong
2014-2023

Rangamati Science and Technology University
2022

Chattogram Veterinary and Animal Sciences University
2022

Automation in every part of life has become a frequent situation because the rapid advancement technology, mostly driven by AI and helped facilitate improved decision‐making. Machine learning deep subset provide machines with capacity to make judgments on their own through continuous process from vast amounts data. To decrease human mistakes while making critical choices improve knowledge game, AI‐based technologies are now being implemented numerous sports, including cricket, football,...

10.1155/2023/2398121 article EN cc-by Computational Intelligence and Neuroscience 2023-01-01

House hunting, or the act of seeking for a place to live, is one most significant responsibilities many families around world. There are numerous criteria/factors that must be evaluated and investigated. These traits can both statistically qualitatively quantified expressed. also hierarchical link between elements. Furthermore, objectively/quantitatively assessing qualitative characteristics difficult, resulting in data inconsistency and, as result, uncertainty. As ambiguity dealt with using...

10.14569/ijacsa.2022.0131091 article EN International Journal of Advanced Computer Science and Applications 2022-01-01

Life is full of emotion. Emotions are short-lived in duration and consist a synchronized set responses, which may contain verbal, physiological, behavioural, neural mechanisms. A motivation for the research ability to simulate empathy. The machine should understand emotional state human being acclimatize its behaviour by giving an appropriate response those emotions. In this we proposed methodology emotion extraction from real time chat messenger. This paper also focuses on implementation...

10.1109/iciev.2014.6850785 article EN 2014-05-01

Now-a-days, online interpersonal communications have become more preferable than face-to-face interactions. However, emotions play a significant role in communication. Automatic extraction of from the text is hot research issue because it minimizes communication gap and misunderstanding between users. To emotionally intelligent, our previous to emotion analyzing system should communicate with experts for suggestions possible emotional state if fails analyze text. In this research, we augment...

10.1109/iccitechn.2014.7073079 article EN 2014-12-01

The expansiveness of the internet encourages people to express their personal feelings via textual medium in terms virtual communication. People are being influenced move into this type communication with remarkable growth social sites, messengers, blogs, micro blogs etc. Automatic derivation emotion from text is a challenge as it minimizes misunderstanding by conveying internal state users. Here we propose an intelligent framework detect text. We divide two modules, namely Training Module...

10.1109/iccitechn.2015.7488104 article EN 2015-12-01

10.1109/iciea61579.2024.10664936 article EN 2022 IEEE 17th Conference on Industrial Electronics and Applications (ICIEA) 2024-08-05

Artificial Intelligence (AI) has paved the way for revolutionary decision-making processes, which if harnessed appropriately, can contribute to advancements in various sectors, from healthcare economics. However, its black box nature presents significant ethical challenges related bias and transparency. AI applications are hugely impacted by biases, presenting inconsistent unreliable findings, leading costs consequences, highlighting perpetuating inequalities unequal access resources. Hence,...

10.48550/arxiv.2408.15550 preprint EN arXiv (Cornell University) 2024-08-28
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