The detection of gender, age, and ethnicity using machine learning techniques holds significant promise for applications in marketing, healthcare, and law enforcement. Previous methods relied on conventional machine l...
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The most serious disease that can affect paddy plants is blast disease. All over the world, it results in enormous yield losses. A fungus that attacks the plant's leaves, nodes, and grains is the main culprit behi...
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ISBN:
(纸本)9789819726134
The most serious disease that can affect paddy plants is blast disease. All over the world, it results in enormous yield losses. A fungus that attacks the plant's leaves, nodes, and grains is the main culprit behind the disease. Fungicides are frequently used to stop blast disease, but this approach has some drawbacks, including environmental pollution and the development of fungicide-resistant disease strains. An effective tool for modeling and managing complex systems, such as the blast disease in paddy plants, is fuzzy logic. In this study, we investigate the modeling and management of blast disease in paddy plants using fuzzy logic. We'll discuss the input variables, fuzzy sets, rule base, and output variables, among other components, that make up the fuzzy logic system. The various phases of fuzzy logic, including fuzzification, inference, and defuzzification, will also be covered. The advantages of using fuzzy logic to manage blast disease in paddy plants, including its capacity to deal with ambiguous and imprecise data and its potential to integrate with other control systems, will be discussed in the final section. The fungal disease known as rice leaf blast, which is having a devastating effect on rice production and quality throughout the globe, thrives in warm, humid environments. Management of rice production relies on precise and non-destructive diagnostic techniques. The use of hyper spectral imaging technologies for diagnosing plant diseases has much promise. The problem with using hyper spectral data to build an effective illness classification model is that it contains a lot of duplicated information. However, a lack of representative features has been gathered due to the complexity and limited scope of agricultural hyper spectral imaging data collection. This paper discussed the four models DenseNet169-MLP, CNN, EfficientNetB3, and DNN JOA. DenseNet169-MLP achieves the highest accuracy 96.52, precision of 100, F1-score 94.29 compared to other model
One of the important technologies for protecting civilian life from terrorist attacks is explosive detection techniques. The global incidence of terrorist activities has been considerably reduced by the development of...
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Generative AI and text-based image synthesis are being pursued with more interest than ever and adopt a growing audience. This work offers a new way of producing images within a broad range of quality levels, deducing...
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The country's economy relies heavily on agriculture, and the health of the crops is essential to its success. Crop diseases that go undetected can cost the agriculture industry. Thus early detection and identifica...
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Recent years have seen innovative advancements in Artificial Intelligence (AI) in the realms of image and video processing, speech and audio recognition, and pattern recognition, leading to the boom in AI art and deep...
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In recent times, in the handling of health facilities, cloud computing performs a big part. Such title is electronic healthcare, used to enhance the efficiency of cloud healthcare. A virtual device for health services...
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Notable tech companies such as Facebook, Microsoft, Apple, Google, and a number of game companies have launched bold plans to bring the metaverse to life. It is inevitable that in the years to come, virtual worlds wil...
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This research explores Decentralized Finance (DeFi) through the lens of enhanced applications, introducing the concept of Decentralized Finance Enhanced (DeFine). It examines the transformative potential of DeFi, anal...
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Artificial neural networks give more promising and accurate results than other methods for prediction, classification, and segmentation engineering problems. The accuracy of the artificial neural network is affected b...
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