Search Results - "Razali, Md Saifullah"

Sarcasm Detection Using Deep Learning With Contextual Features by Razali, Md Saifullah, Halin, Alfian Abdul, Ye, Lei, Doraisamy, Shyamala, Norowi, Noris Mohd

“…Our work focuses on detecting sarcasm in tweets using deep learning extracted features combined with contextual handcrafted features. A feature set is…”
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Context-Driven Satire Detection With Deep Learning by Razali, Md Saifullah, Abdul Halin, Alfian, Chow, Yang-Wai, Mohd Norowi, Noris, Doraisamy, Shyamala

“…This work discuss the task of automatically detecting satire instances in short articles. It is the study of extracting the most optimal features by using a…”
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An analysis of MVL neural operators using feed forward backpropagation: Realization and application of logic synthesis by Chowdhury, Adib Kabir, Saifullah Razali, Md, Wyai, Gary Loh Chee, Gopal, Lenin, Madon, Bakri, Singh, Ashutosh Kumar

“…In this paper, a Neural Network Deployment (NND) algorithm is presented to realize and synthesize Multi-Valued Logic (MVL) functions. The algorithm is combined…”
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Deep Learning Metaphor Detection with Emotion-Cognition Association by Razali, Md Saifullah, Halin, Alfian Abdul, Chow, Yang-Wai, Norowi, Noris Mohd, Doraisamy, Shyamala

“…The focal point of this work is to automatically detect metaphor instances in short texts. It is the study of extricating the most optimal features for the…”
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The importance of multimodality in sarcasm detection for sentiment analysis by Razali, Md Saifullah, Halin, Alfian Abdul, Norowi, Noris Mohd, Doraisamy, Shyamala C.

“…Sentiment analysis is the computational study of opinions given by the users of online media platforms e.g. Twitter, Facebook, Instagram. The output will be in…”
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Sarcasm Detection Using Deep Learning With Contextual Features by Razali, Md Saifullah, Halin, Alfian Abdul, Ye, Lei, Doraisamy, Shyamala, Norowi, Noris Mohd

“…Our work focuses on detecting sarcasm in tweets using deep learning extracted features combined with contextual handcrafted features. A feature set is…”
Get full text