With the rapid development of all walks of life, engineering personnel to AC servo control system performance requirements more and more high. In order to improve the accuracy and response speed of the servo control s...
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Web crawlers, also known as web spiders or web robots, are automated programs that systematically browse the World Wide Web, indexing web pages and gathering data for various purposes. This paper addresses the ineffic...
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Automatic material sorting is widely used in enterprise automatic production line, product assembly line and automated warehouse. Compared with traditional manual sorting, automatic sorting has the advantages of high ...
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In this paper, a video crowd anomaly detection and classification method based on Markov model is proposed. The anomaly detection in crowd is defined as different abnormal targets in dense crowd, and on this basis, a ...
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The K-nearest neighbor (KNN) algorithm is widely used in navigation, such as traffic management, driverless vehicles, and logistics planning. While it offers powerful instance-based learning, its performance can be in...
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One of the major challenges in the world is to control the impacts of global warming and greenhouse gas emissions on the environment. To reduce CO2 emission, an environment friendly substitute for traditional fossil f...
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This paper emphases onto development and enhancement of text generation models using transformer architectures, specifically GPT-2. The designed system focuses on three key models: (1) a baseline GPT-2 model, (2) an o...
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Inefficient garbage collection not only leads to overflowing bins and unpleasant but also poses significant environmental and health risks. This paper proposes an effective garbage monitoring system utilizing a GSM mo...
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The deaf-blind community faces significant challenges in identifying banknotes due to simultaneous hearing and vision impairments, which complicate their ability to conduct daily financial transactions. Recent advance...
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The issue of transparency in diagnostic methods has been a crucial challenge in Alzheimer's Disease detection. This paper focuses on analyzing state-of-art deep learning algorithms namely, customized convolutional...
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