Machine Learning
Packet delivery ratio data collected for the article Wireless-Sensor Network Topology Optimization in Complex Terrain: A Bayesian Approach. Published in the IEEE Internet of Things Journal.
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The data set contains inspections conducted by the Norwegian Labour Inspection Authority (NLIA) between 2012 and 2019. Each row in the dataset contains a control point, non-compliance indicator for the control point and industry code / municipality / county of the inspected organisation.
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The "RetroRevMatchEvalICIP16" dataset provides a retrospective reviewer recommendation dataset and evaluation for IEEE ICIP 2016. The methodology via which the recommendations were obtained and the evaluation was performed is described in the associated paper.
Y. Zhao, A. Anand, and G. Sharma, “Reviewer recommendations using document vector embeddings and a publisher database: Implementation and evaluation,” IEEE Access, vol. 10, pp. 21 798–21 811, 2022. https://doi.org/10.1109/ACCESS.2022.3151640
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This is a dataset is an example of a distribution of 20 correlated Bernoulli random variables.
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Microwave-based breast cancer detection is a growing field that has been investigated as a potential novel method for breast cancer detection. Breast microwave sensing (BMS) systems use low-powered, non-ionizing microwave signals to interrogate the breast tissues. While some BMS systems have been evaluated in clinical trials, many challenges remain before these systems can be used as a viable clinical option, and breast phantoms (breast models) allow for rigorous and controlled experimental investigations.
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This dataset is a hand noted dataset that consists of two categories, evasion and normal methods. By evasion methods we mean the methods that are used by Android malware to hide their malicious payload, and hinder the dynamic analysis. Normal methods are any other methods that cannot be used as evasion techniques. Also, the evasion methods are categorized into six categories: File access, Integrity check, Location, SMS, Time, Anti-emulation. This dataset can be used by any ML or DL approaches to predict new evasion techniques that can be used by malware to hinder the dynamic analysis.
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In this paper, the security-aware robust resource allocation in energy harvesting cognitive radio networks is considered with cooperation between two transmitters while there are uncertainties in channel gains and battery energy value. To be specific, the primary access point harvests energy from the green resource and uses time switching protocol to send the energy and data towards the secondary access point (SAP).
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1.Visualization of convolutional neural network layers for one participant at ROI 301 * 301
2.Convolutional neural network structure analysis in Matlab
3.Convolutional neural network Matlab code
4.Videos of brightness mode (B-mode) ultrasound images from two participants during the recorded walking trials at 5 different speeds
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DIDA is a new image-based historical handwritten digit dataset and collected from the Swedish historical handwritten document images between the year 1800 and 1940. It is the largest historical handwritten digit dataset which is introduced to the Optical Character Recognition (OCR) community to help the researchers to test their optical handwritten character recognition methods. To generate DIDA, 250,000 single digits and 200,000 multi-digits are cropped from 75,000 different document images.
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