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1
Persian Sentence-level Sentiment Polarity Classification
In: ICOTEN ; https://hal.archives-ouvertes.fr/hal-03258138 ; ICOTEN, Jun 2021, Glasgow, United Kingdom (2021)
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2
Persian Sentence-level Sentiment Polarity Classification
In: ICOTEN ; https://hal.archives-ouvertes.fr/hal-03241928 ; ICOTEN, May 2021, Glasgow, France (2021)
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3
Extending persian sentiment lexicon with idiomatic expressions for sentiment analysis
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4
Novel Deep Convolutional Neural Network-Based Contextual Recognition of Arabic Handwritten Scripts
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5
A novel context-aware multimodal framework for persian sentiment analysis
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6
A semi-supervised approach for sentiment analysis of arab (ic+ izi) messages: Application to the algerian dialect
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7
A Semi-supervised Approach for Sentiment Analysis of Arab(ic+izi) Messages: Application to the Algerian Dialect
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8
A Novel Context-Aware Multimodal Framework for Persian Sentiment Analysis
Dashtipour, Kia; Gogate, Mandar; Cambria, Erik. - : Elsevier BV, 2021
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9
Novel Deep Convolutional Neural Network-Based Contextual Recognition of Arabic Handwritten Scripts
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10
Persian Sentence-level Sentiment Polarity Classification
Dashtipour, Kia; Gogate, Mandar; Gelbukh, Alexander. - : IEEE, 2021. : Piscataway, NJ, USA, 2021
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11
CochleaNet: A robust language-independent audio-visual model for real-time speech enhancement
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12
Offline Arabic Handwriting Recognition Using Deep Machine Learning: A Review of Recent Advances
Abstract: In pattern recognition, automatic handwriting recognition (AHWR) is an area of research that has developed rapidly in the last few years. It can play a significant role in broad-spectrum of applications rending from, bank cheque processing, application forms processing, postal address processing, to text-to-speech conversion. However, most research efforts are devoted to English-language only. This work focuses on developing Offline Arabic Handwriting Recognition (OAHR). The OAHR is a very challenging task due to some unique characteristics of the Arabic script such as cursive nature, ligatures, overlapping, and diacritical marks. In the recent literature, several effective Deep Learning (DL) approaches have been proposed to develop efficient AHWR systems. In this paper, we commission a survey on emerging AHWR technologies with some insight on OAHR background, challenges, opportunities, and future research trends.
Keyword: Deep Learning; Offline Arabic database; Offline Arabic Handwritten Recognition
URL: https://doi.org/10.1007/978-3-030-39431-8_44
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13
Deep Neural Network Driven Binaural Audio Visual Speech Separation
Gogate, Mandar; Dashtipour, Kia; Bell, Peter. - : Institute of Electrical and Electronics Engineers, 2020
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14
Visual Speech In Real Noisy Environments (VISION): A Novel Benchmark Dataset and Deep Learning-Based Baseline System
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15
A hybrid Persian sentiment analysis framework: Integrating dependency grammar based rules and deep neural networks
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16
A Hybrid Persian Sentiment Analysis Framework: Integrating Dependency Grammar Based Rules and Deep Neural Networks ...
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17
Lip-reading driven deep learning approach for speech enhancement
In: abs/1808.00046 ; 1 ; 10 (2019)
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18
A Hybrid Persian Sentiment Analysis Framework: Integrating Dependency Grammar Based Rules and Deep Neural Networks
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19
Persian Named Entity Recognition
Dashtipour, Kia; Gogate, Mandar; Adeel, Ahsan. - : Institute of Electrical and Electronics Engineers Inc, 2017. : Piscataway, NJ, USA, 2017
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