Antenna optimization using machine learning is a rapidly evolving field that leverages the power of artificial intelligence to design and improve antenna systems. Antenna optimization is a process of modifying antenna...
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Emotion detection is one of the crucial topics of Natural Language Processing (NLP) in recent years, and now one of the biggest motivating factors in correct identification and interpretation of a wide range of emotio...
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Detecting and promptly identifying cracks on road surfaces is of paramount importance for preserving infrastructure integrity and ensuring the safety of road users, including both drivers and pedestrians. Presently, t...
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This systematic review gave special attention to diabetes and the advancements in food and nutrition needed to prevent or manage diabetes in all its forms. There are two main forms of diabetes mellitus: Type 1 (T1D) a...
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Text summarization is a fundamental Natural language processing task that plays a crucial role in efficiently condensing large textual documents into concise and clear summaries for human comprehension. The amount of ...
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Brain signal analysis from electroencephalogram(EEG)recordings is the gold standard for diagnosing various neural disorders especially epileptic *** signals are highly chaotic compared to normal brain signals and thus...
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Brain signal analysis from electroencephalogram(EEG)recordings is the gold standard for diagnosing various neural disorders especially epileptic *** signals are highly chaotic compared to normal brain signals and thus can be identified from EEG *** the current seizure detection and classification landscape,most models primarily focus on binary classification—distinguishing between seizure and non-seizure *** effective for basic detection,these models fail to address the nuanced stages of seizures and the intervals between *** identification of per-seizure or interictal stages and the timing between seizures is crucial for an effective seizure alert *** granularity is essential for improving patient-specific interventions and developing proactive seizure management *** study addresses this gap by proposing a novel AI-based approach for seizure stage classification using a Deep Convolutional Neural Network(DCNN).The developed model goes beyond traditional binary classification by categorizing EEG recordings into three distinct classes,thus providing a more detailed analysis of seizure *** enhance the model’s performance,we have optimized the DCNN using two advanced techniques:the Stochastic Gradient Algorithm(SGA)and the evolutionary Genetic Algorithm(GA).These optimization strategies are designed to fine-tune the model’s accuracy and ***,k-fold cross-validation ensures the model’s reliability and generalizability across different data *** and validated on the Bonn EEG data sets,the proposed optimized DCNN model achieved a test accuracy of 93.2%,demonstrating its ability to accurately classify EEG *** summary,the key advancement of the present research lies in addressing the limitations of existing models by providing a more detailed seizure classification system,thus potentially enhancing the effectiveness of real-time seizure prediction and management systems in clinic
With the profound use of digital contents in education and social media, multimedia content have become a prevalent means of communication and with such rapid increase, information security is still a major concern. T...
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In 2018, there were 1 million occurrences of non-melanoma cancer and 288,000 occurrences of malignant skin cancer (MM) recorded worldwide. Given the aging of the population and limited resources for medical care, a co...
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This survey paper explores recent advancements in neural rendering, focusing on the development and impact of Neural Radiance Fields (NeRF). Initially, 3D reconstruction relied on methods such as Photogrammetry, Struc...
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The escalating sophistication of counterfeit face currency demands innovative solutions for robust detection. In this study, we propose LBPNET, a novel approach employing Local Binary Pattern (LBP) feature extraction ...
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