His primary areas of investigation include Sentiment analysis, Artificial intelligence, Data science, Natural language processing and Natural language. His Sentiment analysis research is multidisciplinary, incorporating elements of Information retrieval, Semantic Web, The Internet, Social media and Affective computing. His research integrates issues of Context and Machine learning in his study of Artificial intelligence.
His studies in Data science integrate themes in fields like Scientometrics, Sentic computing, Multi-agent system and Knowledge base. His Natural language processing study combines topics in areas such as Emotion recognition, Polarity, Inference and Handwriting. His work deals with themes such as Semantics and Ambiguity, which intersect with Natural language.
Amir Hussain mostly deals with Artificial intelligence, Sentiment analysis, Machine learning, Speech recognition and Natural language processing. His Artificial intelligence study frequently links to other fields, such as Pattern recognition. Amir Hussain interconnects Semantic Web, Social media, Semantics, Natural language and Data science in the investigation of issues within Sentiment analysis.
His Speech recognition research incorporates elements of Artificial neural network, Speech enhancement and Adaptive filter. The concepts of his Artificial neural network study are interwoven with issues in Control theory and Nonlinear system. His biological study spans a wide range of topics, including Active noise control and Wiener filter.
Artificial intelligence, Deep learning, Natural language processing, Convolutional neural network and Pattern recognition are his primary areas of study. His research on Artificial intelligence often connects related areas such as Machine learning. The Deep learning study which covers Pattern recognition that intersects with MNIST database.
His Natural language processing study incorporates themes from Named-entity recognition and Arabic. His Pattern recognition research integrates issues from Feature, Robustness and Electroencephalography. His research investigates the connection with Sentiment analysis and areas like Social media which intersect with concerns in Public health.
His scientific interests lie mostly in Artificial intelligence, Deep learning, Machine learning, Artificial neural network and Benchmark. His research in Artificial intelligence intersects with topics in Pattern recognition, Speech recognition and Natural language processing. His Natural language processing research focuses on Sentiment analysis in particular.
The various areas that Amir Hussain examines in his Deep learning study include Background noise, Convolutional neural network, Supervised learning, Perceptron and Multilayer perceptron. His Artificial neural network research is multidisciplinary, incorporating perspectives in Algorithm and Kernel. His studies deal with areas such as Preprocessor and Baseline system as well as Benchmark.
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A review of affective computing
Soujanya Poria;Erik Cambria;Rajiv Bajpai;Amir Hussain.
Information Fusion (2017)
Agent-based computing from multi-agent systems to agent-based models: a visual survey
Muaz Niazi;Amir Hussain.
Fusing audio, visual and textual clues for sentiment analysis from multimodal content
Soujanya Poria;Erik Cambria;Newton Howard;Guang-Bin Huang.
Enhanced SenticNet with Affective Labels for Concept-Based Opinion Mining
S. Poria;A. Gelbukh;A. Hussain;N. Howard.
IEEE Intelligent Systems (2013)
Applications of Deep Learning and Reinforcement Learning to Biological Data
Mufti Mahmud;Mohammed Shamim Kaiser;Amir Hussain;Stefano Vassanelli.
IEEE Transactions on Neural Networks (2018)
Sentic Computing: Techniques, Tools, and Applications
Erik Cambria;Amir Hussain.
SenticNet: A Publicly Available Semantic Resource for Opinion Mining
Erik Cambria;Robert Speer;Catherine Havasi;Amir Hussain.
national conference on artificial intelligence (2010)
Group sparse regularization for deep neural networks
Simone Scardapane;Danilo Comminiello;Amir Hussain;Aurelio Uncini.
Convolutional MKL Based Multimodal Emotion Recognition and Sentiment Analysis
Soujanya Poria;Iti Chaturvedi;Erik Cambria;Amir Hussain.
international conference on data mining (2016)
The hourglass of emotions
Erik Cambria;Andrew Livingstone;Amir Hussain.
COST'11 Proceedings of the 2011 international conference on Cognitive Behavioural Systems (2011)
(Impact Factor: 4.89)
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