14 citations · 47 across the 6 of their papers we have counts for
8 papers
sarcasm detection and quantification in arabic tweets
Bashar Talafha, Muhy Eddin Za'ter, Samer Suleiman +2
The role of predicting sarcasm in the text is known as automatic sarcasm detection. Given the prevalence and challenges of sarcasm in sentiment-bearing text, this is a critical pha…
The 2ST-UNet for Pneumothorax Segmentation in Chest X-Rays using ResNet34 as a Backbone for U-Net
Ayat Abedalla, Malak Abdullah, Mahmoud Al-Ayyoub +1
Pneumothorax, also called a collapsed lung, refers to the presence of the air in the pleural space between the lung and chest wall. It can be small (no need for treatment), or larg…
Predicting Helpfulness of Online Reviews
Abdalraheem Alsmadi, Shadi AlZu'bi, Mahmoud Al-Ayyoub +1
E-commerce dominates a large part of the world's economy with many websites dedicated to online selling products. The vast majority of e-commerce websites provide their customers w…
Tha3aroon at NSURL-2019 Task 8: Semantic Question Similarity in Arabic
Ali Fadel, Ibraheem Tuffaha, Mahmoud Al-Ayyoub
In this paper, we describe our team's effort on the semantic text question similarity task of NSURL 2019. Our top performing system utilizes several innovative data augmentation te…
Neural Arabic Text Diacritization: State of the Art Results and a Novel Approach for Machine Translation
Ali Fadel, Ibraheem Tuffaha, Bara' Al-Jawarneh +1
In this work, we present several deep learning models for the automatic diacritization of Arabic text. Our models are built using two main approaches, viz. Feed-Forward Neural Netw…
Arabic Text Diacritization Using Deep Neural Networks
Ali Fadel, Ibraheem Tuffaha, Bara' Al-Jawarneh +1
Diacritization of Arabic text is both an interesting and a challenging problem at the same time with various applications ranging from speech synthesis to helping students learning…
A detailed comparative study of open source deep learning frameworks
Ghadeer Al-Bdour, Raffi Al-Qurran, Mahmoud Al-Ayyoub +1
Deep Learning (DL) is one of the hottest trends in machine learning as DL approaches produced results superior to the state-of-the-art in problematic areas such as image processing…
On the Use of Emojis to Train Emotion Classifiers
Wegdan Hussien, Mahmoud Al-Ayyoub, Yahya Tashtoush +1
Nowadays, the automatic detection of emotions is employed by many applications in different fields like security informatics, e-learning, humor detection, targeted advertising, etc…