Signal Processing
Anomaly detection plays a crucial role in various domains, including but not limited to cybersecurity, space science, finance, and healthcare. However, the lack of standardized benchmark datasets hinders the comparative evaluation of anomaly detection algorithms. In this work, we address this gap by presenting a curated collection of preprocessed datasets for spacecraft anomalies sourced from multiple sources. These datasets cover a diverse range of anomalies and real-world scenarios for the spacecrafts.
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762 Views
This dataset is associated with the injection of false data into solar-powered insecticidal lamps, primarily aimed at reporting false data injection attacks on the Solar insecticidal lamps-Internet of Things (SIL-IoTs). The data was collected on the campus of Nanjing Agricultural University, gathering two types of data from the insecticidal lamp device of Chengdu Biang Technology Co., Ltd. and our team's self-developed insecticidal lamp device (insect count and sound signal data, respectively). The insect count data is in text format and has not been processed.
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54 Views
This data was recorded for emg based force/Torque estimation. EMG and torque signals were collected during simultaneous, isometric, but continuously varying contractions, corresponding to two wrist DoF. The experiment was carried out in two trials with a 5-min rest in between. Each trial included six combinations of tasks, separated by 2 min of rest to minimize the effect of fatigue. The performed tasks were categorized into individual and combined (simultaneous) DoF to test the ability to estimate isolated torque and torque in two simultaneous DoF.
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230 Views
The dataset consists of experimental data collected in an anechoic tank, with a specific setup involving single-source transmission and reception by a 6-element circular array with a radius of 0.046 meters. The transmitted signals include common wideband signals used in underwater positioning and communication, such as chirps, single-carrier QPSK, multi-tone signals, and OFDM signals. The transmitter and receiver are located at the same depth, and the receiving array rotates 360 degrees with 30-degree intervals.
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246 Views
The "Thaat and Raga Forest (TRF) Dataset" represents a significant advancement in computational musicology, focusing specifically on Indian Classical Music (ICM). While Western music has seen substantial attention in this field, ICM remains relatively underexplored. This manuscript presents the utilization of Deep Learning models to analyze ICM, with a primary focus on identifying Thaats and Ragas within musical compositions. Thaats and Ragas identification holds pivotal importance for various applications, including sentiment-based recommendation systems and music categorization.
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701 Views
Video super-resolution (SR) has important real world applications such as enhancing viewing experiences of legacy low-resolution videos on high resolution display devices. However, there are no visual quality assessment (VQA) models specifically designed for evaluating SR videos while such models are crucially important both for advancing video SR algorithms and for viewing quality assurance. Therefore, we establish a super-resolution video quality assessment database （VSR-QAD） for implementing super-resolution video quality assessment.
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192 Views
The Dominica database is used to evaluate and compare the performance of sperm whale click detectors. The database consists of 3 hours of recordings of sperm whale echolocation clicks and 4 hours of sound recordings containing delphinid clicks and transients from different sound sources, but no sperm whale clicks.
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425 Views
Video super-resolution (SR) has important real world applications such as enhancing viewing experiences of legacy low-resolution videos on high resolution display devices. However, there are no visual quality assessment (VQA) models specifically designed for evaluating SR videos while such models are crucially important both for advancing video SR algorithms and for viewing quality assurance. Therefore, we establish a super-resolution video quality assessment database （VSR-QAD） for implementing super-resolution video quality assessment.
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32 Views
Video super-resolution (SR) has important real world applications such as enhancing viewing experiences of legacy low-resolution videos on high resolution display devices. However, there are no visual quality assessment (VQA) models specifically designed for evaluating SR videos while such models are crucially important both for advancing video SR algorithms and for viewing quality assurance. Therefore, we establish a super-resolution video quality assessment database （VSR-QAD） for implementing super-resolution video quality assessment.
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46 Views
This dataset contains RF (Radio Frequency) signals obtained from simulations, which model ultrasound propagation in cortical bone.
The simulations were designed to provide insights into the behaviour of ultrasound waves in cortical bone tissues, both in intact and pathological conditions. The dataset covers a wide range of parameters, including varying thickness (1-8 mm), porosity (1-20%), and frequency (1-8 MHz), allowing to explore the impact of these factors on ultrasound signal characteristics.
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337 Views