Artificial Intelligence

The detection and recognition of road traffic signs and panel guide content has become challenging in recent years. Few studies have been made to solve these two issues at the same time, especially in the Arabic language. Additionally, the limited number of datasets for traffic signs and panel guide content makes the investigation more interesting. In our work, we propose a Deep Active Learning Approach for Traffic Sign and Panel Guide Arabic-Latin Text Content Annotation in Natural Scene Images.

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Transistor models are crucial for circuit simulation. Reliable design of high-performance circuits requires that transistor characteristics are adequately represented, which makes accurate and fast models indispensable. Scattering (or S-)parameters are perhaps the most widely used RF characteristics, employed in the design and analysis of linear devices and circuits for calculation of the input and output impedance, isolation, gain, as well as stability, all being important performance figures for small-signal or low-noise amplifiers.

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The dataset includes the device geometries and the corresponding performance. The device geometries consist of four-dimensional factors (L, W, T, H) and the device performance consists of three-dimensional parameters (R, S, δl).

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Simultaneously-collected multimodal Mannequin Lying pose (SMaL) dataset is a infant pose dataset based on a posable mannequin. The SMaL dataset contains a set of 300 unique poses under three cover conditions using three sensor modalities: color imaging, depth sensing, and pressure sensing. It represents the first multimodal dataset for infant pose estimation and the first dataset to explore under the cover pose estimation for infants.

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This is the dataset we collected for the article "Scalable Undersized Dataset RF Classification: Using Convolutional Multistage Training". 17 objects were collected in the laboratory and scanned using a 'cw radar' setup featuring 2x UWB antennas (1 transmit antenna, 1 receive antenna), inside anechoic chamber. There was no clutter added in the experiment.

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We uploaded the raw collected fish image data used for model training. These data were divided into those in simple and complex background. In total, there are more than 800 images.

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This dataset includes real-world Channel Quality Indicator (CQI) values from UEs connected to real commercial networks in Greece. In total, we collected CQI data from 74 cars that drive through a specific road in the city of Volos, Greece. This dataset is part of our following work:

 

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This cherry tree disease detection dataset is a multimodal, multi-angle dataset which was constructed for monitoring the growth of cherry trees, including stress analysis and prediction. An orchard of cherry trees is considered in the area of Western Macedonia, where 577 cherry trees were recorded in a full crop season starting from Jul. 2021 to Jul. 2022. The dataset includes a) aerial / Unmanned Aerial Vehicle (UAV) images, b) ground RGB images/photos, and c) ground multispectral images/photos.

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This dataset contains bone scan image and its segmentation mask. The segmentation mask is made for the purpose of detecting metastases on bone scan images

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We create a thermal infrared face dataset (TIF) for fever screening. TIF is collected at the entrance of our university’s engineering building. The infrared face images are captured by an infrared camera under different environmental conditions.

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