Supply chain management Constantly encounters challenges for instance service duplication, Indigent Collaboration among various Divisions, and absence of formal procedures, leading to lucidity issues. The prevalence o...
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Human motion prediction aims to predict future human motion based on past observations, playing important roles in several fields. However, previous works have often focused on the temporal sequential nature of human ...
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A scene in a video consists of several shots and difference between shot and scene is that shot is captured from different camera locations whereas scene consists of shots that are captured at same location but from d...
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This research introduces an innovative approach to early detection of visual defects in children, integrating deep learning models (ResNet-50, VGG-19, EfficientNet) through transfer learning for enhanced diagnostic ac...
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The standard researching trend in Natural Language Processing scales down to sentiment analysis in various Indian languages. This analysis is frequently used to get more information about public opinion, analyze custo...
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In today's world, many technologically innovative solutions are developed to prioritize women's safety solutions, especially during nighttime. This research's main aim is to focus on addressing crucial saf...
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In Vehicular Edge Computing (VEC), efficient task offloading is essential for reducing latency and enhancing system performance, especially in resource-constrained environments. In this regard, Roadside Units (RSUs) c...
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Involving integrated development environments (IDEs) in introductory-level (CS1) programming courses is critical. However, it is difficult for instructors to find a suitable IDE that is beginner-friendly and offers ro...
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Recently, a vast amount of text data has increased rapidly and therefore information must be summarised to retrieve useful knowledge. First, the preprocessing module utilises the fixed-length stemming method, and then...
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Agriculture, a crucial foundation for human existence, exists at the intersection of conventional methods and modern innovations. Any country's primary issue in agriculture science is effective plant disease contr...
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ISBN:
(纸本)9798331519056
Agriculture, a crucial foundation for human existence, exists at the intersection of conventional methods and modern innovations. Any country's primary issue in agriculture science is effective plant disease control, driven by the growing need for food due to population growth. Moreover, developments in modern technology have greatly improved the precision and effectiveness of plant detection. A critical challenge in the agricultural sector is leaf diseases, significantly impacting crop production and economic profit. Integrating digitalization and technology in agriculture is imperative for augmenting productivity and ensuring food security. This research emphasizes the principal concerns and obstacles associated with classifying leaf diseases. By experimenting with different approaches, researchers have already achieved great strides in the identification and categorization of illnesses. But due to assessments, new information, and discussions, changes are required. The resilience of deep learning (DL) and machine learning (ML) techniques, such as feed-forward neural networks (FFNN), k-means clustering (KMC), fuzzy logic (FL), artificial neural networks (ANN), and genetic algorithms (GA),so forth, has been demonstrated by earlier research. Due to their inherent ability to automatically obtain relevant visual information and understand spatial hierarchies, CNNs are usually the preferred option for image identification and classification among the ML and DL methods addressed in this study. The selection between machine learning and deep learning is dependent upon numerous issues, the data that is available, and the amount of processing power that is available. Because of this, DL - primarily using CNNs are advised for many complicated image detection and classification applications. They also show outstanding results for classification and detection on their datasets but not on others. Lastly, by using a variety of methods for processing images in the field of artif
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