The work adds towards sentiment analysis by introducing an understanding lexicon and BERT based NLP model XLNet. Based on fundamental research and systematic practice in Design Phase, the lexicon describes the benefit...
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This study focuses on development of a secure and efficient image cryptosystem optimized for IoT devices. The proposed technique addresses the and resource constraints of IoT devices, it introduces a hybrid encryption...
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Diabetic Foot Ulcer (DFU) is a severe complication of diabetes, frequently resulting in amputation and having a significant impact on patients' quality of life. Early and accurate DFU classification is essential f...
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The segmentation of the polyps during colonoscopy is one of the most crucial factors for successful colon cancer diagnosis. Due to the wide variety of sizes and shapes of these polyps, this process can be challenging....
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DifEvoDenseFed is introduced as an innovative solution for Alzheimer's disease prediction, leveraging the combined strengths of Differential Evolution Optimization (DifEvo), DenseNet, and Federated Learning (Fed)....
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ISBN:
(纸本)9798350319088
DifEvoDenseFed is introduced as an innovative solution for Alzheimer's disease prediction, leveraging the combined strengths of Differential Evolution Optimization (DifEvo), DenseNet, and Federated Learning (Fed). The urgency of Alzheimer's as a global health concern necessitates accurate early detection for effective intervention. In this advanced model, DenseNet forms the cornerstone, capitalizing on its proficiency in image-based tasks. At the client level, Differential Evolution Optimization (DifEvo) fine-tunes model parameters locally, adapting to the unique characteristics of each dataset. This individualized optimization enhances precision and ensures adaptability across diverse data sources. The collaboration between multiple clients is orchestrated by Federated Learning, preserving data privacy and decentralizing the learning process. Clients retain control of their sensitive medical data, reducing privacy risks associated with centralized systems. This decentralized approach improves scalability and fault tolerance. The synergy of these components culminates in a robust and accurate Alzheimer's prediction model. Local Differential Evolution (DifEvo) optimizations refine parameters, which are aggregated at a central server to iteratively enhance the global model. This process ensures ongoing model improvement while minimizing communication overhead. Moreover, the versatility of this approach extends beyond Alzheimer's prediction, making it suitable for various medical image analysis tasks. It fosters community collaboration among healthcare institutions, promoting a collective effort to combat Alzheimer's disease. It is important to note that the model's effectiveness is contingent upon data quality, system design, and DifEvo's optimization capabilities. Rigorous validation and evaluation are essential to measure its real-world impact. 'DifEvoDenseFed' marks a significant stride in early Alzheimer's detection, privacy-preserving AI in healthcare, and collab
With the increasing prevalence of digital documents in various domains, the demand for efficient and accurate question-answering (QA) systems has grown significantly. Traditional QA models primarily focus on text-base...
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The resolution and implementation of constrained optimization problems consistently remain a prominent subject in the realm of contemporary complex engineering applications. In this paper, the amalgamation of extracti...
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Identifying human actions and postures presents significant challenges for computerized systems. The categorization of these tasks holds particular relevance in the fields of health and robotics. Leveraging artificial...
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A methodology for cloud-native development called serverless facilitates the creation and execution of programmes by developers without worrying about maintaining servers. As no automation is available to implement Fa...
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Sentiment analysis is becoming increasingly beneficial to monitor social media, allowing us to obtain insight into public opinion surrounding certain topics. Long Short-Term Memory (LSTM) has been widely applied in se...
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