Machine Learning
The analysis is based on two kinds of measured dataset. In both cases, uplink data are measured (A-UL0) i.e. the transmitters are UBSs and the receiver is UBSC and FDD is used. The first dataset has been collected from August 17, 2018, to August 20, 2018. The experiment has been carried over two separate distances, i.e., 1 km, and 3 km between the transmitter (Tx) and receiver (Rx) in Mohang Port (Taean-gun).
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Supplementary materials of the paper titled
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We obtained 6 million instances to be used as an analysis for modelling CO2 behavior. The Data Logging and sensors nodes acquisition are every 1 second.
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Pedestrian detection has never been an easy task for computer vision and automotive industry. Systems like the advanced driver assistance system (ADAS) highly rely on far infrared (FIR) data captured to detect pedestrians at nighttime. The recent development of deep learning-based detectors has proven the excellent results of pedestrian detection in perfect weather conditions. However, it is still unknown what is the performance in adverse weather conditions.
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The data set includes three sub-data sets, namely the DAGM2007 data set, the ground crack data set, and the Yibao bottle cap defect data set, which are divided into a training set and a test set, in which the positive and negative samples are unbalanced.
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