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Anam Shahil-Feroz, Haleema Yasmin, Sarah Saleem, Zulfiqar Bhutta and Emily Seto
This study assessed the usability of the smartphone app, named ?Raabta? from the perspective of pregnant women at high risk of preeclampsia to improve the Raabta app for future implementation. Think-aloud and task-completion techniques were used with a p...
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Lal Khan, Ammar Amjad, Kanwar Muhammad Afaq and Hsien-Tsung Chang
Sentiment analysis (SA) has been an active research subject in the domain of natural language processing due to its important functions in interpreting people?s perspectives and drawing successful opinion-based judgments. On social media, Roman Urdu is o...
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Sana Shams and Muhammad Aslam
Detecting the communicative intent behind user queries is critically required by search engines to understand a user?s search goal and retrieve the desired results. Due to increased web searching in local languages, there is an emerging need to support t...
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Bilal Ahmed Chandio, Ali Shariq Imran, Maheen Bakhtyar, Sher Muhammad Daudpota and Junaid Baber
Deep neural networks have emerged as a leading approach towards handling many natural language processing (NLP) tasks. Deep networks initially conquered the problems of computer vision. However, dealing with sequential data such as text and sound was a n...
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Sehrish Munawar Cheema, Muhammad Ali, Ivan Miguel Pires, Norberto Jorge Gonçalves, Mustahsan Hammad Naqvi and Maleeha Hassan
The agriculture sector is the backbone of Pakistan?s economy, reflecting 26% of its GPD and 43% of the entire labor force. Smart and precise agriculture is the key to producing the best crop yield. Moreover, emerging technologies are reducing energy cons...
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Faria Ferooz, Malik Tahir Hassan, Sajid Mahmood, Hira Asim, Muhammad Idrees, Muhammad Assam, Abdullah Mohamed and El-Awady Attia
To reduce crime rates, there is a need to understand and analyse emerging patterns of criminal activities. This study examines the occurrence patterns of crimes using the crime dataset of Lahore, a metropolitan city in Pakistan. The main aim is to facili...
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Tharindu Ranasinghe and Marcos Zampieri
The pervasiveness of offensive content in social media has become an important reason for concern for online platforms. With the aim of improving online safety, a large number of studies applying computational models to identify such content have been pu...
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Amber Baig, Mutee U Rahman, Hameedullah Kazi and Ahsanullah Baloch
Processing of social media text like tweets is challenging for traditional Natural Language Processing (NLP) tools developed for well-edited text due to the noisy nature of such text. However, demand for tools and resources to correctly process such nois...
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Mujtaba Husnain, Malik Muhammad Saad Missen, Shahzad Mumtaz, Muhammad Zeeshan Jhanidr, Mickaël Coustaty, Muhammad Muzzamil Luqman, Jean-Marc Ogier and Gyu Sang Choi
In the area of pattern recognition and pattern matching, the methods based on deep learning models have recently attracted several researchers by achieving magnificent performance. In this paper, we propose the use of the convolutional neural network to ...
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Mohammad Ali Humayun, Ibrahim A. Hameed, Syed Muslim Shah, Sohaib Hassan Khan, Irfan Zafar, Saad Bin Ahmed and Junaid Shuja
Automatic Speech Recognition, (ASR) has achieved the best results for English, with end-to-end neural network based supervised models. These supervised models need huge amounts of labeled speech data for good generalization, which can be quite a challeng...
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