Potato cultivation is a vital component of global agriculture, providing a significant source of nutrition and income. However, the threat of diseases affecting potato crops remains a persistent challenge for farmers....
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We demonstrated a MOSCAP silicon microring modulator integrated with high-mobility titanium-doped indium oxide, achieving sub-volt 0.8 Vpp modulation up to 25 Gb/s, marking a milestone in transparent conducting oxide ...
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Interference estimation and mitigation are of high importance in many applications of array signal processing. State-of-the-art angle and direction estimation techniques for digital arrays often rely on computationall...
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Campus safety is a paramount concern in educational institutions worldwide, especially in combating the prevalence of campus violence. This comprehensive review utilizes advanced image processing and computer vision t...
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Crop diseases have a significant impact on plant growth and can lead to reduced *** methods of disease detection rely on the expertise of plant protection experts,which can be subjective and dependent on individual ex...
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Crop diseases have a significant impact on plant growth and can lead to reduced *** methods of disease detection rely on the expertise of plant protection experts,which can be subjective and dependent on individual experience and *** address this,the use of digital image recognition technology and deep learning algorithms has emerged as a promising approach for automating plant disease *** this paper,we propose a novel approach that utilizes a convolutional neural network(CNN)model in conjunction with Inception v3 to identify plant leaf *** research focuses on developing a mobile application that leverages this mechanism to identify diseases in plants and provide recommendations for overcoming specific *** models were trained using a dataset consisting of 80,848 images representing 21 different plant leaves categorized into 60 distinct *** rigorous training and evaluation,the proposed system achieved an impressive accuracy rate of 99%.This mobile application serves as a convenient and valuable advisory tool,providing early detection and guidance in real agricultural *** significance of this research lies in its potential to revolutionize plant disease detection and management *** automating the identification process through deep learning algorithms,the proposed system eliminates the subjective nature of expert-based diagnosis and reduces dependence on individual *** integration of mobile technology further enhances accessibility and enables farmers and agricultural practitioners to swiftly and accurately identify diseases in their crops.
By creating a sophisticated virtual assistant (VA), this study investigates how generative AI might revolutionise human-machine interaction (HMI). Our suggested solution overcomes conventional constraints by utilising...
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Heart failure is one of the serious worldwide health issue which requires early identification and treatment. The paper offers an ensemble machine learning model that incorporates various patient variables, such as de...
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The Qur’an holds immense theological and historical significance, and developing a technology-driven solution for answering questions from this sacred text is of paramount importance. This paper presents our approach...
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Tracking attendance in educational institutions is an extremely time-consuming and labor-intensive process, and the task seems to be plagued by inaccuracies and inefficiencies at all times. Techniques such as manual r...
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Skin problems are common health issues around the world, and effective treatment frequently requires an accurate and prompt diagnosis. The objective of this work is to use federated learning to enable dermoscopic anal...
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