Artificial Intelligence
The region-based segmentation approach has been a major research area for many medical image applications. A vision guided autonomous system has used region-based segmentation information to operate heavy machinery and locomotive machines intended for computer vision applications. The dataset contains raw images in .png format fro brain tumor in various portions of brain.The dataset can be used fro training and testing. Images are calssified into three main regions as frontal lobe(level -1, level-2), optus-lobe(level-1), medula_lobe(level-1,level-2,level-3).
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Context
This dataset consists of subject wise daily living activity data, which is acquired from the inbuilt accelerometer and gyroscope sensors of the smartphones.
Content
The smartphone was mounted on the waist and front pockets of the users. All the different activities were performed in a laboratory except Running, which was performed on a Football Playground.
Smartphone used: Poco X2 and Samsung Galaxy A32s
Inbuild Sensors used: Accelerometer and Gyroscope
Ages: All subjects are Above 23 years
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In the simulation experiment, OPNET simulation software was used to simulate the Space-Integrated Ground Information Intelligent Network environment to obtain the data. A satellite network composed of six satellites was used to simulate the data flow formed by the ground communication traffic through this network. The simulated time was one week and the traffic data information of a node was randomly collected for analysis and learning.
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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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279 Views
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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The files contain the trained networks (Alexnet, Resnet 18, VGG19, and SRN) for classify the upsampled quadrant data by wavelength.
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40 Views
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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Source code for the paper "On the Implementation of Behavior Trees in Robotics"
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The CoVID19-FNIR dataset contains news stories related to CoVID-19 pandemic fact-checked by expert fact-checkers. CoVID19-FNIR is a CoVID-19-specific dataset consisting of fact-checked fake news scraped from Poynter and true news from the verified Twitter handles of news publishers. The data samples were collected from India, The United States of America, and European regions and consist of online posts from social media platforms between February 2020 to June 2020. The dataset went through prepossessing steps that include removing special characters and non-vital information.
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6317 Views
The accompanying dataset for the CVSports 2021 paper: DeepDarts: Modeling Keypoints as Objects for Automatic Scoring in Darts using a Single Camera
Paper Abstract:
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