Machine Learning
Text classification systems have become increasingly important in recent years due to the explosion of online documents and the need to sort them for specific services. One of the most critical issues in text classification is the limited availability and diversity of datasets, which can lead to overfitting and poor generalization. In this context, we present a new dataset named Global News 60K (GN60K), which consists of 60,000 news articles from different sources from different parts of the world, covering 10 topics.
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A long-standing problem in thermal imaging is the inherent assumption of a uniform and known emissivity across an entire image. Semantic segmentation of the materials in a thermal image can identify the pixel-wise emissivity, thus rectifying the spatially uniform emissivity assumption with no human intervention. We have created a multispectral thermal image dataset consisting of nine materials (acrylic, aluminum, bakelite, ceramic, cork, EVA, granite, maple, and silicone) at six different temperatures.
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Smart homes contain programmable electronic devices (mostly IoT) that enable home automation. People who live in smart homes benefit from interconnected devices by controlling them either remotely or manually/autonomously. However, high interconnectivity comes with an increased attack surface, making the smart home an attractive target for adversaries. NCC Group and the Global Cyber Alliance recorded over 12,000 attacks to log into smart home devices maliciously. Recent statistics show that over 200 million smart homes can be subjected to these attacks.
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Around from 12th century MODI script was used to write Indian languages as Marathi, Hindi, and Gujarati etc. It was used as administrative script from 17th century to mid of 19th century in Maharashtra state (India). At present, MODI script users are diminishing away, and countable persons can understand the MODI script. The preserved archaic historical MODI handwritten documents contained important and rare cultural, historic, and administrative kind of information which is usable in present-days.
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MODI script was used to write Indian languages as Marathi, Hindi, and Gujarati etc. from 12th century. From 17th century to mid of 19th century MODI was used as administrative script in Maharashtra state (India). Now a days, MODI script users are diminishing away, and countable persons can understand the MODI script. The archaic historical MODI handwritten documents contained important and rare cultural, historic, and administrative type of information which is usable in current era.
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The dataset consists of measurements of different stages of degradation in low-voltage contactors used for industrial purposes. The measurements were obtained with fiber Bragg grating (FBG) sensors that detect the dynamic deformation generated in switching under different load conditions and internal components. The posted dataset was preprocessed and separated into two different events. The signal is segmented and reduced from the original measurement (separated into opening and closing). Furthermore, two sets of measurements were obtained.
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On the basis of autonomous mobile tea picking robot, aiming at the shortcomings of traditional tea bud identification methods such as slow speed, low accuracy and poor adaptability, as well as people's demand for high-quality tea, the research and experiment of tea bud quality classification recognition based on YOLOv5 were carried out. Through the construction of the autonomous mobile tea picking robot visual recognition system, the data set was constructed, which mainly included tea image acquisition, enhancement and annotation.
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On the basis of autonomous mobile tea picking robot, aiming at the shortcomings of traditional tea bud identification methods such as slow speed, low accuracy and poor adaptability, as well as people's demand for high-quality tea, the research and experiment of tea bud quality classification recognition based on YOLOv5 were carried out. Through the construction of the autonomous mobile tea picking robot visual recognition system, the data set was constructed, which mainly included tea image acquisition, enhancement and annotation.
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Global Illumination (GI) is a strategy in computer graphics to add a certain degree of realism. Several approaches exist to achieve such a visual effect for computer-generated imagery. The most physically accurate approach is through conventional raytracing. It produces similar realistic results by trading-off time and computational-resource intensive, making them unsuitable for real-time usage. For more real-time usage scenarios, a set of faster algorithms exists that utilize post-processing on top of rasterization rather than performing ray-tracing.
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This experiment was implemented to collect infrared images of the coal and gangue samples at the temperature of 323.15 K. Additionally, it showed that distinguishing between coal and gangue samples is feasible, although the area, thickness, and surface conditions were changed at a constant temperature during the process of capturing the infrared images. The coal and gangue were randomly collected from the same mine. The random samples had different weights, shapes, areas, thicknesses, and surface conations.
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