Sarcasm Detection Using Deep Learning With Contextual Features
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DOI: 10.1109/access.2021.3076789
Abstract: Our work focuses on detecting sarcasm in tweets using deep learning extracted features combined with contextual handcrafted features. A feature set is extracted from a Convolutional Neural Network (CNN) architecture before it is combined with… read more here.
Keywords: sarcasm detection; detection using; feature sets; using deep ... See more keywords
Context-Driven Satire Detection With Deep Learning
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DOI: 10.1109/access.2022.3194119
Abstract: 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 deep learning architecture combined with carefully handcrafted contextual features.… read more here.
Keywords: driven satire; context driven; deep learning; feature sets ... See more keywords
Smart Analysis of Economics Sentiment in Spanish Based on Linguistic Features and Transformers
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DOI: 10.1109/access.2023.3244065
Abstract: Texts related to economics and finances are characterized by the use of words and expressions whose meaning (and the sentiments they convey) substantially depend on the context. This poses a major challenge to Natural Language… read more here.
Keywords: economics; analysis; feature sets; linguistic features ... See more keywords
Breast Microcalcification Diagnosis Using Deep Convolutional Neural Network from Digital Mammograms
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DOI: 10.1155/2019/2717454
Abstract: Mammography is successfully used as an effective screening tool for cancer diagnosis. A calcification cluster on mammography is a primary sign of cancer. Early researches have proved the diagnostic value of the calcification, yet their… read more here.
Keywords: diagnosis; feature sets; calcification; deep features ... See more keywords
Inter-Residue Distance Prediction From Duet Deep Learning Models
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Genetics"
DOI: 10.3389/fgene.2022.887491
Abstract: Residue distance prediction from the sequence is critical for many biological applications such as protein structure reconstruction, protein–protein interaction prediction, and protein design. However, prediction of fine-grained distances between residues with long sequence separations still… read more here.
Keywords: inter residue; distance prediction; prediction; residue distance ... See more keywords