In this paper we propose to investigate feature vector learning of images with pretrained models with an aim to classify them. We further show that clustering based on these feature vectors is much superior to that pe...
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Soil moisture content (SMC) is influenced by a variety of environmental factors. Recent studies have demonstrated that integrating LoRa-RSSI data with environmental parameters can enhance the accuracy of soil moisture...
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Removing noise in digital images is a fundamental operation that arises in many application domains. In this paper we consider the median filter, a filtering technique that replaces the color of each pixel with the me...
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Cryptographic protocols are used to relax the ever-developing quantity of linked gadgets that make up the net of things (IoT). Those cryptographic protocols have been designed to make certain that IoT tool traffic sta...
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Photovoltaic systems are being used more and more in the production of electricity because of the high cost of fossil fuel-based energy. The main issue that happens between grid and end-user transmission lines is powe...
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Industrial automation has become a cornerstone of modern manufacturing, enhancing efficiency, reliability, and scalability. The integration of intelligent control algorithms, such as fuzzy logic, neural networks, gene...
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Many existing anomaly detection methods on attributed networks do not seriously tackle the inherent multi-view property in attribute space but concatenate multiple views into a single feature vector, which inevitably ...
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A major problem especially in urban areas is traffic congestion which causes increased travel times, pollution, and compromises safety. This paper presents the design of the Smart Traffic light timing Management Syste...
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To enhance the super-resolution reconstruction quality of remote sensing images, this paper fully consider the multi-scale nature of internal features and proposes a multi-scale multi-level fusion network. This networ...
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The detection of small lesions on grape leaves plays a pivotal role in the early identification and management of plant diseases, potentially reducing significant agricultural losses. Traditional detection systems, in...
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