Global potato production is at risk because of potato leaf diseases, which cause huge economic losses. To ensure crop productivity and disease management, their efficient and accurate localization is of utmost importa...
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This paper explores the harnessed potential of machine intelligence algorithms in the domain of plant disease detection. Agriculture remains the cornerstone of economic development, especially in countries like India....
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An unsupervised spoken term discovery task aims to capture the pattern similarities among spoken terms in the absence of annotation. Such an approach is useful for the untranscribed spoken content from low-resource or...
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Images are a crucial source of information and are also used as a legal references and proofs sometimes, but since the availability of it has made easy due to internet hence it is prone to many manipulations and tampe...
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The rapid evolution of e-learning platforms necessitates the development of innovative methods to enhance learner engagement. This study leverages machine learning (ML) techniques and models to predict e-learning enga...
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Digital image processing plays a crucial part in the detection, observation, and diagnosis of a brain tumor. From MRI images, automatic detection of a brain tumors is perhaps the most difficult and critical task in pr...
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There are learning aids available for those who are deaf or have trouble speaking or hearing, but they are rarely used. Live sign motions would be handled via image processing in the suggested system, which would oper...
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Facial Expression Recognition (FER) is a vital area of research in affective computing, permitting systems to automatically interpret and respond to human emotions by studying and analyzing facial expressions. FER inv...
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Purpose-Chronic diseases are considered as one of the serious concerns and threats to public health across the *** such as chronic diabetes mellitus(CDM),cardio vasculardisease(CVD)and chronic kidney disease(CKD)are m...
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Purpose-Chronic diseases are considered as one of the serious concerns and threats to public health across the *** such as chronic diabetes mellitus(CDM),cardio vasculardisease(CVD)and chronic kidney disease(CKD)are major chronic diseases responsible for millions of *** of these diseases is considered as a risk factor for the other two ***,noteworthy attention is being paid to reduce the risk of these *** amount of medical data is generated in digital form from smart healthcare appliances in the current *** numerous machine learning(ML)algorithms are proposed for the early prediction of chronic diseases,these algorithmic models are neither generalized nor adaptive when the model is imposed on new disease ***,these algorithms have to process a huge amount of disease data iteratively until the model *** limitation may make it difficult forMLmodels to fit and produce imprecise results.A single algorithm may not yield accurate ***,an ensemble of classifiers built from multiple models,that works based on a voting principle has been successfully applied to solve many classification *** purpose of this paper is to make early prediction of chronic diseases using hybrid generative regression based deep intelligence network(HGRDIN)***/methodology/approach-In the proposed paper generative regression(GR)model is used in combination with deep neural network(DNN)for the early prediction of chronic *** GR model will obtain prior knowledge about the labelled data by analyzing the correlation between features and class ***,the weight assignment process of DNN is influenced by the relationship between attributes rather than random *** knowledge obtained through these processes is passed as input to the DNN network for further *** the inference about the input data instances is drawn at the DNN through the GR model,the model is named as
In the Quantum Computing field, the CHSH (Clauser-Horne-Shimony-Holt) game plays a vital role in determining whether a system is in classical or quantum domain. This quantum advantage property is applied in determinin...
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