Image captioning has seen significant research efforts over the last *** goal is to generate meaningful semantic sentences that describe visual content depicted in photographs and are syntactically *** real-world appl...
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Image captioning has seen significant research efforts over the last *** goal is to generate meaningful semantic sentences that describe visual content depicted in photographs and are syntactically *** real-world applications rely on image captioning,such as helping people with visual impairments to see their *** formulate a coherent and relevant textual description,computer vision techniques are utilized to comprehend the visual content within an image,followed by natural language processing *** approaches and models have been developed to deal with this multifaceted *** models prove to be stateof-the-art solutions in this *** work offers an exclusive perspective emphasizing the most critical strategies and techniques for enhancing image caption *** than reviewing all previous image captioning work,we analyze various techniques that significantly improve image caption generation and achieve significant performance improvements,including encompassing image captioning with visual attention methods,exploring semantic information types in captions,and employing multi-caption generation ***,advancements such as neural architecture search,few-shot learning,multi-phase learning,and cross-modal embedding within image caption networks are examined for their transformative *** comprehensive quantitative analysis conducted in this study identifies cutting-edgemethodologies and sheds light on their profound impact,driving forward the forefront of image captioning technology.
The highly infectious and mutating COVID-19, known as the novel coronavirus, poses a substantial threat to both human health and the global economy. Detecting COVID-19 early presents a challenge due to its resemblance...
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Prediction systems are an important aspect of intelligent *** engineering practice,the complex system structure and the external environment cause many uncertain factors in the model,which influence the modeling accur...
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Prediction systems are an important aspect of intelligent *** engineering practice,the complex system structure and the external environment cause many uncertain factors in the model,which influence the modeling accuracy of the *** belief rule base(BRB)can implement nonlinear modeling and express a variety of uncertain information,including fuzziness,ignorance,randomness,***,the BRB system also has two main problems:Firstly,modeling methods based on expert knowledge make it difficult to guarantee the model’s ***,interpretability is not considered in the optimization process of current research,resulting in the destruction of the interpretability of *** balance the accuracy and interpretability of the model,a self-growth belief rule basewith interpretability constraints(SBRB-I)is *** reasoning process of the SBRB-I model is based on the evidence reasoning(ER)***,the self-growth learning strategy ensures effective cooperation between the datadriven model and the expert system.A case study showed that the accuracy and interpretability of the model could be *** SBRB-I model has good application prospects in prediction systems.
Cloud is based on the underlying technology of virtualization. Here, the physical servers are divided into multiple virtual servers. Through the technology of virtualization, each virtual server contains virtual machi...
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The South Indian mango industry is confronting severe threats due to various leaf diseases,which significantly impact the yield and quality of the *** management and prevention of these diseases depend mainly on their...
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The South Indian mango industry is confronting severe threats due to various leaf diseases,which significantly impact the yield and quality of the *** management and prevention of these diseases depend mainly on their early identification and accurate *** central objective of this research is to propose and examine the application of Deep Convolutional Neural Networks(CNNs)as a potential solution for the precise detection and categorization of diseases impacting the leaves of South Indian mango *** study collected a rich dataset of leaf images representing different disease classes,including Anthracnose,Powdery Mildew,and Leaf *** maintain image quality and consistency,pre-processing techniques were *** then used a customized deep CNN architecture to analyze the accuracy of South Indian mango leaf disease detection and *** proposed CNN model was trained and evaluated using our collected *** customized deep CNN model demonstrated high performance in experiments,achieving an impressive 93.34%classification *** result outperformed traditional CNN algorithms,indicating the potential of customized deep CNN as a dependable tool for disease *** proposed model showed superior accuracy and computational efficiency performance compared to other basic CNN *** research underscores the practical benefits of customized deep CNNs for automated leaf disease detection and classification in South Indian mango *** findings support deep CNN as a valuable tool for real-time interventions and improving crop management practices,thereby mitigating the issues currently facing the South Indian mango industry.
The current study is defined by two main aims. An effective strategy for improving local search is to combine the Set Algebra-Based Heuristic Algorithm (SAHA) algorithm with the Nelder-Mead simplex method. The approac...
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This paper aims to construct and analyze the conforming and nonconforming virtual element methods for a class of fourth order nonlinear Schrodinger equations with trapped *** mainly consider three types of virtual ele...
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This paper aims to construct and analyze the conforming and nonconforming virtual element methods for a class of fourth order nonlinear Schrodinger equations with trapped *** mainly consider three types of virtual elements,including H^(2) conforming virtual element,C^(0) nonconforming virtual element and Morley-type nonconforming virtual *** fully discrete schemes are constructed by virtue of virtual element methods in space and modified Crank-Nicolson method in *** prove the mass and energy conservation,the boundedness and the unique solvability of the fully discrete *** introducing a new type of the Ritz projection,the optimal and unconditional error estimates for the fully discrete schemes are presented and ***,two numerical examples are investigated to confirm our theoretical analysis.
In this study, we utilize a recently proposed non-parametric metaheuristic algorithm known as geometric mean optimization (GMO) to adjust the hidden layer input weights and bias of six ANN variants, namely PSNN, SPNN,...
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The security of smart contract has always been one of the significant problems in blockchain. As shown in previous studies, vulnerabilities in smart contracts can lead to unpredictable losses. With the rapid growth of...
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Purpose-The paper aims to introduce an efficient routing algorithm for wireless sensor networks(WSNs).It proposes an improved evaporation rate water cycle(improved ER-WC)algorithm and outlining the systems performance...
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Purpose-The paper aims to introduce an efficient routing algorithm for wireless sensor networks(WSNs).It proposes an improved evaporation rate water cycle(improved ER-WC)algorithm and outlining the systems performance in improving the energy efficiency of *** proposed technique mainly analyzes the clustering problem of WSNs when huge tasks are ***/methodology/approach-This proposed improved ER-WC algorithm is used for analyzing various factors such as network cluster-head(CH)energy,CH location and CH density in improved *** proposed study will solve the energy efficiency and improve network throughput in ***-This proposed work provides optimal clustering method for Fuzzy C-means(FCM)where efficiency is improved in *** evaluations are conducted to find network lifespan,network throughput,total network residual energy and network *** limitations/implications-The proposed improved ER-WC algorithm has some implications when different energy levels of node are used in *** implications-This research work analyzes the nodes’energy and throughput by selecting correct CHs in intra-cluster *** can possibly analyze the factors such as CH location,network CH energy and CH ***/value-This proposed research work proves to be performing better for improving the network throughput and increases energy efficiency for WSNs.
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