optimizationtheory serves as a pivotal scientific instrument for achieving optimal system performance, with its origins in economic applications to identify the best investment strategies for maximizing benefits. Ove...
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In recent years, as neural networks continue to evolve, the use of YOLO deep learningalgorithms in medical imaging and diagnosis has become increasingly prevalent. the detection and recognition of blood cells are cru...
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ISBN:
(纸本)9798400716645
In recent years, as neural networks continue to evolve, the use of YOLO deep learningalgorithms in medical imaging and diagnosis has become increasingly prevalent. the detection and recognition of blood cells are crucial aspects of medical diagnosis. While deep learning-based object detection and recognition are garnering increasing interest, detecting and counting blood cells in medical imaging remains an essential and challenging task. In this paper, we optimize and improve the YOLOv5 algorithm to achieve efficient detection and recognition of peripheral blood cells. We begin by outlining the architecture and the training procedures of YOLOv5 and discuss its potential applications in medical imaging. Building on the characteristics of blood cell images, we introduce an optimization method using DenseNet based on YOLOv5. Enhancements in data preprocessing, network structuring, and training parameters have improved the accuracy and efficiency of blood cell recognition and counting. Experiments conducted on our proprietary dataset and subsequent comparisons withthe base algorithm affirm our claims. Results suggest that our proposed method demonstrates strong performance in detecting and identifying blood cells, offering high practicality for applications.
作者：
Wanjari, KetanVerma, Prateek
Department of Computer Science and Engineering Faculty of Engineering and Technology Maharashtra Wardha442001 India
Department of Artificial Intelligence and Data Science Faculty of Engineering and Technology Maharashtra Wardha442001 India
Modern image recognition has experienced dramatic improvements because of Machine learning and Deep learningalgorithms together. this study investigates CNNs and SVMs for recognition enhancement while reviewing image...
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the proceedings contain 281 papers. the topics discussed include: deep learning for sentiment analysis;a review on advances in sentiment analysis: a deep learning approach using transformer based models;a grading mode...
ISBN:
(纸本)9798331523923
the proceedings contain 281 papers. the topics discussed include: deep learning for sentiment analysis;a review on advances in sentiment analysis: a deep learning approach using transformer based models;a grading model for jasmine flowers using deep learning and quantum machine learning;deep learning-based algorithm for feature recognition in the construction process of decorative materials;a review on the applications of machine learning and deep learningalgorithms for image recognition;streamlining financial predictions: a web application for stock, cryptocurrency, and market sentiment analysis;sentiment and tone analysis of reddit posts using python;deep learning based diagnosis of gum infection and tooth alignment using dental x-ray;and exploring sentiment and moral dynamics in children's literature using machine learning: a sentiment analysis approach
the modern times have led to the adoption of distinctive meta-heuristic procedures for solving distinct class of optimization-problems. the meta-heuristics procedures have benefit above conventional algorithms because...
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the integration of renewable energy sources into power systems has introduced complexities that necessitate advanced optimization strategies for efficient energy management. this paper presents a novel deep learning-b...
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Deep learning (DL) has emerged as a powerful tool in the field of remote sensing, particularly for processing images captured by unmanned aerial vehicles (UAVs). While it has yielded significant contributions across v...
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Reinforcement learning (RL) has been widely used in various real-world applications, such as robotics, game playing, and finance. However, traditional RL algorithms exhibit limitations in training efficiency and perfo...
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this research study integrates machine learning and fuzzy logic methodologies to improve resource allocation and task scheduling in an AWS-based medical database. the ANN model has the highest performance with 0.9676 ...
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Machine learningalgorithms have become pervasive in diverse applications, revolutionizing various domains. However, the abundance of algorithms, each designed for specific purposes, poses a challenge for both novice ...
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