Indian agriculture is striving to achieve sustainable intensification,the system aiming to increase agricultural yield per unit area without harming natural resources and the *** farming employs technology to improve ...
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Indian agriculture is striving to achieve sustainable intensification,the system aiming to increase agricultural yield per unit area without harming natural resources and the *** farming employs technology to improve *** and accurate analysis and diagnosis of plant disease is very helpful in reducing plant diseases and improving plant health and food crop *** disease experts are not available in remote areas thus there is a requirement of automatic low-cost,approachable and reliable solutions to identify the plant diseases without the laboratory inspection and expert’s *** learning-based computer vision techniques like Convolutional Neural Network(CNN)and traditional machine learning-based image classification approaches are being applied to identify plant *** this paper,the CNN model is proposed for the classification of rice and potato plant leaf *** leaves are diagnosed with bacterial blight,blast,brown spot and tungro *** leaf images are classified into three classes:healthy leaves,early blight and late blight *** leaf dataset with 5932 images and 1500 potato leaf images are used in the *** proposed CNN model was able to learn hidden patterns from the raw images and classify rice images with 99.58%accuracy and potato leaves with 97.66%*** results demonstrate that the proposed CNN model performed better when compared with other machine learning image classifiers such as Support Vector Machine(SVM),K-Nearest Neighbors(KNN),Decision Tree and Random Forest.
Environmental sustainability is crucial for ensuring the long-term health and well-being of our planet and its in-habitants. Precise navigation of autonomous and semi-autonomous vehicles in agricultural usage, therefo...
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Alzheimer’s dementia (AD) poses a significant global health challenge, characterized by progressive cognitive decline, memory impairment, and behavioral changes. The critical need for early detection to enable timely...
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作者：
Xu, ZeliangKim, Dong InWoo, Simon S.
Department of Computer Science and Engineering Suwon16419 Korea Republic of
Department of Electrical and Computer Engineering Suwon16419 Korea Republic of
This paper proposes a novel cloud-edge collaborative distributed diffusion model for AI-generated content (AIGC) such as image generation, which integrates adaptive clustering techniques with dynamic step-size optimiz...
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A new health concern in recent periods has seen the evolution of uncertain sedentary *** sedentary for extended durations is regarded as a notable hazard across various adult age brackets,especially the excessive depe...
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A new health concern in recent periods has seen the evolution of uncertain sedentary *** sedentary for extended durations is regarded as a notable hazard across various adult age brackets,especially the excessive dependence on automobiles for *** the active period,monitoring seating habits has been made easier by ***,there exists a disagreement among professionals regarding the most suitable quantifiable criteria for encompassing the comprehensive data on sedentary behavior throughout the *** to variations in measurement methodologies,data analysis approaches,and the lack of essential outcome indicators such as the total sedentary duration,the assessment of sedentary patterns in numerous research investigations was considered *** research suggested fleeting granularity distinguish occurrences of regular human *** units(essential cells) acquire multivariate transitory *** Behavior Patterns(FBPs) can be identified with a estimation of timeframe using our proposed scalable algorithms that employ collected widespread multivariate data(fleeting granularity).The research outcome,supported by rigorous analyses on two validated datasets,mark a significant *** the final stages of the study,a stacked Long Short-Term Memory(LSTM) model was utilized to replicate and forecast repetitive sedentary behavior patterns,leveraging data from the preceding six-hour window blocks of sedentary *** model effectively replicated state traits,previous action sequences,and duration,attaining an impressive 99% accuracy level as assessed through RMSE,MSE,MAPE,and r-correlation metrics.
We design sensitivity oracles for error-prone networks. For a network problem Π, the data structure preprocesses a network G = (V, E) and sensitivity parameter f such that, for any set F ⊆ V ∪ E of up to f link or n...
Glioblastoma is a highly aggressive and malignant brain tumor type that requires early diagnosis and prompt intervention. Due to its heterogeneity in appearance, developing automated detection approaches is challengin...
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Robots are becoming more prevalent and consequently utilized in numerous fields due to the latest advancements in artificial intelligence. Recent studies have shown promise in the human-robot interaction where non-exp...
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An essential component of the diagnostic and treatment process is identifying brain tumors early in their onslaught. Traditional approaches struggle with processing sequential data and face limitations in maintaining ...
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Sentiment Analysis Systems (SASs) are data-driven Artificial Intelligence (AI) systems that assign one or more numbers to convey the polarity and emotional intensity of a given piece of text. However, like other autom...
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