In the realm of computer vision, image denoising remains a formidable challenge with profound implications for fields like medical imaging, remote sensing, and photography. Despite notable advancements in deep learnin...
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A smart city is a fast-moving terrain that requires efficient and smart security mechanisms with resilience for solving the intricate challenges of modern urbanism. The current paper presents the critical review of ma...
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In this article we propose to detect the hand and face gestures in a peer to peer video call. First the frames are captured from webcam using openCV, then hand and facial landmarks in video frames are detected using M...
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Social media is a platform where people express their opinions through user-generated text. Investigating opinion changes of people based on the influence of legitimate users and bots over time is crucial. The influen...
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Antimicrobial resistance (AMR) is one of the significant problems in the health sector and requires resources to create and develop accurate forecasting systems capable of recognizing resistant microbes and their trea...
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Air pollution presents significant health and ecological dangers, especially in densely populated urban regions. This study looks at the current models that are used to guess the Air Quality Index (AQI). It does this ...
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Real-Time Hand Gesture Recognition Using Convolutional Neural Networks: A Robust Approach for Diverse Applications. Hand gestures are fundamental to human communication and find extensive utility across various domain...
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Free speech is essential, but it can conflict with protecting marginalized groups from harm caused by hate speech. Social media platforms have become breeding grounds for this harmful content. While studies exist to d...
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Free speech is essential, but it can conflict with protecting marginalized groups from harm caused by hate speech. Social media platforms have become breeding grounds for this harmful content. While studies exist to detect hate speech, there are significant research gaps. First, most studies used text data instead of other modalities such as videos or audio. Second, most studies explored traditional machine learning algorithms. However, due to the increase in complexities of computational tasks, there is need to employ complex techniques and methodologies. Third, majority of the research studies have either been evaluated using very few evaluation metrics or not statistically evaluated at all. Lastly, due to the opaque, black-box nature of the complex classifiers, there is need to use explainability techniques. This research aims to address these gaps by detecting hate speech in English and Kiswahili languages using videos manually collected from YouTube. The videos were converted to text and used to train various classifiers. The performance of these classifiers was evaluated using various evaluation and statistical measurements. The experimental results suggest that the random forest classifier achieved the highest results for both languages across all evaluation measurements compared to all classifiers used. The results for English language were: accuracy 98%, AUC 96%, precision 99%, recall 97%, F1 98%, specificity 98% and MCC 96% while the results for Kiswahili language were: accuracy 90%, AUC 94%, precision 93%, recall 92%, F1 94%, specificity 87% and MCC 75%. These results suggest that the random forest classifier is robust, effective and efficient in detecting hate speech in any language. This also implies that the classifier is reliable in detecting hate speech and other related problems in social media. However, to understand the classifiers’ decision-making process, we used the Local Interpretable Model-agnostic Explanations (LIME) technique to explain the
This paper introduces a browser-based tool for modeling applications with Process Line Diagrams (PLDs)[1]. The tool aims at providing a modular and logical approach for building process architecture models to bridge t...
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Underwater Wireless Sensor Networks (UWSNs) are gaining importance for a wide range of applications, from environmental monitoring to underwater exploration. However, the challenging underwater environment poses signi...
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