The creation of a Real-Time Task Manager with a user-friendly interface and effective system monitoring is presented in this work utilising Python. The Psutil library was used to retrieve comprehensive system informat...
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Sentiment analysis is a significant area of study that concentrates on gathering and examining people's attitudes, feelings, and views about various things, including goods, services, and themes. The approach has ...
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This paper introduces a novel ensemble Spike Timing Dependent Plasticity (EnsembleSTDP) approach for implementing Spiking Neural Networks (SNNs) with on-chip, online (in-situ) unsupervised learning to accelerate train...
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The automatic segmentation of abdominal organs in CT images is a critical task in medical image processing, aiding in improved diagnosis, treatment planning, and disease monitoring. However, due to blurred organ bound...
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In recent years, significant advancements in health-care analytics have shown immense potential in enhancing patient care and clinical decision-making. This research delves into innovative methods for precise migraine...
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This paper presents a deep learning framework to automate recognition of medical prescriptions by using handwritten content, feature extraction from CNNs like VGG16, Alex Net, and MobileNetV2, and sequential data util...
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ChatGPT features anthropomorphic dialogue generation and supports multiple rounds of dialogue, making it suitable for teaching spoken English online. This study utilizes ChatGPT to reconstruct texts with different CEF...
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Agricultural supply chains face specific challenges in ensuring that produce is efficiently categorized, processed, and transported from farmers to end consumers. One of the key difficulties lies in accurately classif...
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ISBN:
(纸本)9798331518943
Agricultural supply chains face specific challenges in ensuring that produce is efficiently categorized, processed, and transported from farmers to end consumers. One of the key difficulties lies in accurately classifying agricultural products based on their quality and characteristics, which directly impacts decision-making processes regarding their handling, storage, and transportation. To address the research gap, this research paper proposes an advanced system that employs a K-means classifier integrated with computer Vision techniques. The K-means algorithm, known for its ability to group data points into distinct clusters, is used here to classify agricultural produce by analysing visual features derived through edge detection and image augmentation. This proposed method enables the system to effectively identify and categorize produce into quality-based clusters, which allows for more targeted and efficient handling procedures. By automating the classification process, this proposed solution significantly reduces human error and its subjectivity in sorting agricultural goods. The system demonstrated a high performance with an overall accuracy of 99.03%, and for certain produce categories, it achieved optimal levels of precision 99.12%, recall 99.03%, and F1-score 99.035% These metrics highlight the system's robustness in differentiating between classes of agricultural produce, ensuring that each product is categorized correctly according to pre-defined standards. The Kmeans classifier, combined with the use of computer Vision techniques, facilitates faster and more reliable decision-making processes, which in turn reduces delays in sorting and transportation. This enhanced classification method not only optimizes resource allocation but also minimizes waste by ensuring that produce is handled in the most efficient manner. Ultimately, the proposed system benefits all stakeholders in the agricultural supply chain, improving operational efficiency, reducing cost
Machine reading comprehension (MRC) is a fundamental natural language understanding task in natural language processing, which aims to comprehend the text of a given passage and answer questions based on it. Understan...
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This research introduces a new approach to radon detection in homes utilizing Decision Trees (DTs) enabled by the cloud in real-time. High radon levels, a natural radioactive gas, are dangerous to human health. Quick ...
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