Artificial Intelligence
The Magnetic Resonance – Computed Tomography (MR-CT) Jordan University Hospital (JUH) dataset has been collected after receiving Institutional Review Board (IRB) approval of the hospital and consent forms have been obtained from all patients. All procedures followed are consistent with the ethics of handling patients’ data.
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1699 Views
Histopathological characterization of colorectal polyps allows to tailor patients' management and follow up with the ultimate aim of avoiding or promptly detecting an invasive carcinoma. Colorectal polyps characterization relies on the histological analysis of tissue samples to determine the polyps malignancy and dysplasia grade. Deep neural networks achieve outstanding accuracy in medical patterns recognition, however they require large sets of annotated training images.
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6015 Views
Blood pressure and heart rate data set collected from Malaysian population.
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680 Views
The boring and repetitive task of monitoring video feeds makes real-time anomaly detection tasks difficult for humans. Hence, crimes are usually detected hours or days after the occurrence. To mitigate this, the research community proposes the use of a deep learning-based anomaly detection model (ADM) for automating the monitoring process.
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852 Views
This datset contains 2000 images of size 256 X256. The dataset is created by captuirng photos using mobile phone. This dataset is applicable for two classes namely water and wet surface.
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1496 Views
This is the dataset provided and collected while "Car Hacking: Attack & Defense Challenge" in 2020. We are the main organizer of the competition along with Culture Makers and Korea Internet & Security Agency. We are very proud of releasing these valuable datasets for all security researchers for free.
The competition aimed to develop attack and detection techniques of Controller Area Network (CAN), a widely used standard of in-vehicle network. The target vehicle of competition was Hyundai Avante CN7.
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10650 Views
Protein molecules are inherently dynamic and modulate their interactions with different molecular partners by accessing different tertiary structures under physiological conditions.Elucidating such structures remains challenging. Current momentum in deep learning and the powerful performance of generative adversarial networks (GANs) in complex domains, such as computer vision, inspires us to investigate GANs on their ability to generate physically-realistic protein tertiary structures.
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655 Views
This data set is the result of model test trained on the basis of the Stanford earthquake dataset (stead): a global data set of seismic signals for AI, which can effectively get the seismic signal and the arrival time of seismic phase from the image, so as to prove the effectiveness of this model
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549 Views
The dataset consists of the ISFET sensor data utilized to train ML models for drift compensation.
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447 Views
A Multi-Agent Approach for Personalized Hypertension Risk Prediction
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435 Views