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Talking Hand: Two Way Communicator for Deaf People

Communication is a basic fundamental human right, and every single person deserves to be a part of the global community. However, those who are deaf or mute, communicate differently than everyone else. Sign language is very important for people who have hearing and speaking deficiency. The only mode of communication for such people to convey […]


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Missing Values Imputation & Classification Using Stream Mining Algorithms in Internet of Things (IoT)

Given the high prevalence and detrimental effects of unintentional falls in the elderly, fall detection has become a pertinent public concern. A Fall Detection System (FDS) gathers information from sensors to distinguish falls from routine activities in order to provide immediate medical assistance. Hence, the integrity of collected data becomes imperative. Presence of missing values […]


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Automated User Requirements Extraction from Reddit Using Machine Learning

There are a lot of social platforms, where thousands of people discuss many topics. Some of the discussions are worthy and rich sources of gathering requirements of applications. Among these, Reddit is a valuable source where a tremendous set of information is erected and can be evaluated for helpful outcomes. Reddit is such a type […]


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Fake News Detection using Machine Learning

Increased connectivity has contributed greatly in facilitating rapid access to information and reliable communication. However, the uncontrolled information dissemination has also resulted in the spread of fake news. Fake news might be spread by a group of people or organizations to serve ulterior motives such as political or financial gains or to damage a country’s […]


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Adverse Drug Reactions (ADRs) extraction using Transfer Of Learning

Adverse drug reactions (ADRs) are the undesirable effects associated with the use of a drug due to some pharmacological action of the drug. During the last few years, social media has become a popular platform where people discuss their health problems and, therefore, has become a popular source to share information related to ADR in […]


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Towards creation of adversarial attacks for textual data from diverse domains

Deep learning is the foundation for various applications, including decision support, fraud detection, text categorization, machine translation, market research, and customer segmentation. Despite their widespread use, deep learning algorithms are frequently vulnerable to adversarial instances, in which legal inputs are manipulated in subtle and often invisible ways. Even the most complicated models may be tricked […]


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Replication of Multi-Agent Reinforcement Learning for Hide & Seek Problem

Reinforcement learning generates policies based on reward functions, hyper-parameters. Slight changes in these can significantly affect results. The lack of documentation and reproducibility in Reinforcement learning research makes it difficult to replicate once-deduced strategies. While previous research has identified strategies using grounded maneuver, there is limited work in the more complex environments. The agents in […]