A sentiment-based product recommendation system is a system that utilizes natural language processing to extract sentiment features from reviews and the machine learning algorithms namely logistic regression, random f...
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The paper introduces a cross-lingual speaker identification system for Indian languages, utilising a Long Short-Term Memory dense neural network (LSTM-DNN). The system was trained on audio recordings in English and ev...
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Electroencephalography (EEG) signals are often utilized to study cognitive processes and brain diseases. The non-stationary and non-linear nature of EEG signals makes their analysis difficult. A deep learning framewor...
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Ultimately, the key to successfully analysing real-world problems is to be diligent and thorough. It is important to carefully consider all available data, remove any redundant or unnecessary information, and approach...
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The Internet has become an essential tool for people in the modern world. Humans, like all living organisms, have essential requirements for survival. These include access to atmospheric oxygen, potable water, protect...
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Deep neural networks have been getting better and better performance while the parameter size has become larger and larger, and have now entered the era of large language models (LLM). However, large language models w...
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Medical Internet of Things (MIoT) and healthcare have lately converged, which has led to novel techniques to identifying and treating medical troubles. This research gives a completely unique method that utilizes the ...
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ISBN:
(纸本)9798350359756
Medical Internet of Things (MIoT) and healthcare have lately converged, which has led to novel techniques to identifying and treating medical troubles. This research gives a completely unique method that utilizes the Internet of Things (IoT) to combine Automatic Modulation Recognition (AMR) with Breast Cancer (BC) categorization. The loss of included answers arises from the reality that most current research ignores BC type in desire for both AMR or BC type. A unique Medical Internet of Things-based totally Breast Cancer (MIoT-BC) category method addresses the project. In order to facilitate automatic modulation identity, the proposed gadget first statistics indicators from clinical gadget and wireless verbal exchange channels. After that, it uses DBNs (deep belief networks) to categorize BCs. The MIoT-primarily based strategy ensures the secure transmission and instantaneous analysis of scientific facts, which improves the precision and timeliness of diagnosis. There are some of blessings to the use of MIoT for BC categorization, such as less difficult get entry to to health information, faster diagnostic instances, and the option for faraway monitoring. In addition, the potential for misclassification and human errors is reduced, making this a useful tool inside the realm of medical diagnostics. DBNs are used to give a dependable and correct type version for BC categorization. Several healthcare packages have found achievement with DBNs due to their suitability for processing excessive-dimensional, complicated scientific facts. Differentiating benign from malignant breast lesions is an area where their capability to extract sizeable facts from enter facts robotically shines. MIoT-primarily based processes the usage of DBNs enhance BC classification accuracy in comparison to traditional techniques, consistent with this paper. Evaluation criteria, such as sensitivity, specificity, accuracy, overall performance and F1 rating, measure the effectiveness of the suggeste
By expanding the Internet in human society, data protection is more needed, because data are vital for some individuals, companies or governments. New technologies, such as big data, the internet of things (IoT), and ...
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Software-defined networking(SDN)represents a paradigm shift in network traffic *** distinguishes between the data and control *** are then used to communicate between these *** controller is central to the management ...
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Software-defined networking(SDN)represents a paradigm shift in network traffic *** distinguishes between the data and control *** are then used to communicate between these *** controller is central to the management of an SDN network and is subject to security *** research shows how a deep learning algorithm can detect intrusions in SDN-based IoT ***,low accuracy,and efficient feature selection is all *** propose a hybrid machine learning-based approach based on Random Forest and Long Short-Term Memory(LSTM).In this study,a new dataset based specifically on Software Defined Networks is used in *** obtain the best and most relevant features,a feature selection technique is *** experiments have revealed that the proposed solution is a superior method for detecting flow-based *** performance of our proposed model is also measured in terms of accuracy,recall,and precision.F1 rating and detection time Furthermore,a lightweight model for training is proposed,which selects fewer features while maintaining the model’s *** show that the adopted methodology outperforms existing models.
Diffusion models have recently emerged as powerful generative models,producing high-fidelity samples across *** this,they have two key challenges,including improving the time-consuming iterative generation process and...
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Diffusion models have recently emerged as powerful generative models,producing high-fidelity samples across *** this,they have two key challenges,including improving the time-consuming iterative generation process and controlling and steering the generation *** surveys provide broad overviews of diffusion model ***,they lack comprehensive coverage specifically centered on techniques for controllable *** survey seeks to address this gap by providing a comprehensive and coherent review on controllable generation in diffusion *** provide a detailed taxonomy defining controlled generation for diffusion *** generation is categorized based on the formulation,methodologies,and evaluation *** enumerating the range of methods researchers have developed for enhanced control,we aim to establish controllable diffusion generation as a distinct subfield warranting dedicated *** this survey,we contextualize recent results,provide the dedicated treatment of controllable diffusion model generation,and outline limitations and future *** demonstrate applicability,we highlight controllable diffusion techniques for major computer vision tasks *** consolidating methods and applications for controllable diffusion models,we hope to catalyze further innovations in reliable and scalable controllable generation.
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