Artificial Intelligence
FormAI is a novel AI-generated dataset comprising 112,000 compilable and independent C programs. All the programs in the dataset were generated by GPT-3.5-turbo using dynamic zero-shot prompting technique and comprises programs with varying levels of complexity. Some programs handle complicated tasks such as network management, table games, or encryption, while others deal with simpler tasks like string manipulation. Each program is labelled based on vulnerabilities present in the code using a formal verification method based on the Efficient SMT-based Bounded Model Checker (ESBMC).
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1804 Views
Most of the current smoke detection techniques are developed using CCTV images. To identify the wildfire early, it can be useful to deploy satellite imagery and develop models that can recognize smoke in forest areas. However, very few labelled satellite image datasets are available to build the wildfire smoke detection model. In order to find a solution to this problem, a dataset consisting 23, 644 satellite images was gathered. The dataset is divided into four categories: smoke, smoke with fog, non-smoke, and non-smoke with fog.
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58 Views
We introduce a high-performance computer vision based Intraveneous (IV) infusion speed measurement system as a camera application on an iPhone or Android phone. Our system uses You Only Look Once version 5 (YOLOv5) as it was designed for real-time object detection, making it substantially faster than two-stage algorithms such as R-CNN. In addition, YOLOv5 offers greater precision than its predecessors, making it more competitive with other object detection methods.
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16 Views
Problems related to ventral hernia are very common, and evaluating them using computational methods can assist in selecting the most appropriate treatment. This study collected data from over 3500 patients from different European countries observed during last 11 years (2012-2022), which were collected by specialists in hernia surgery. The majority of patients underwent standard surgical procedures, with a growing trend towards robotic surgery. This paper focuses on statistically evaluating the treatment methods in relation to patient age, body mass index (BMI), and the type of repair.
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230 Views
This dataset focuses on cooperative spectrum sensing in a cognitive radio network, where multiple secondary users collaborate to detect the presence of a primary user. We introduce multiple cooperative spectrum sensing schemes based on a tree deep neural network architecture, incorporating a one-dimensional convolutional neural network and a long short-term memory network. The primary objective of these schemes is to effectively learn the activity pattern of the primary user.
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1244 Views
Text classification systems have become increasingly important in recent years due to the explosion of online documents and the need to sort them for specific services. One of the most critical issues in text classification is the limited availability and diversity of datasets, which can lead to overfitting and poor generalization. In this context, we present a new dataset named Global News 60K (GN60K), which consists of 60,000 news articles from different sources from different parts of the world, covering 10 topics.
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197 Views
In the current field of multi-view polarization 3D reconstruction, existing datasets primarily fall into two categories: real-world dataset and synthetic dataset. Real-world datasets provide accurate acquisition of illumination from real-world environments, but requires complex setups and specialized equipment such as polarization cameras. Furthermore, specific environmental conditions, such as special lighting conditions or reflective properties, may be difficult to replicate precisely in reality.
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336 Views
— Medical image segmentation is a crucial aspect of medical image processing, and has been widely used in the detection and clinical diagnosis for brain, lung, liver, heart and other diseases. In this paper, we propose a novel multimodal mutual attention network, called MMAUNet, for medical image segmentation. MMA-UNet is divided into two parts. The first part obtains more highdimensional features by skip connection and improved network structure.
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277 Views
Optical coherence tomography (OCT) is a non-invasive imaging technique that has extensive clinical applications in ophthalmology. OCT enables the visualization of the retinal layers, playing a vital role in the early detection and monitoring of retinal diseases.
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2504 Views
The data set is collected from volunteers from Beijing University Third Hospital. FootScan plantar pressure measurement system is used to record the continuous pressure information. The volunteer is familiar with the whole walking process and is asked to walk on the plate with an order of "left foot, right foot, and then left foot," using comfortable walking speed. Volunteers should always ensure the heel touches the plate before the toe during walking. The sampling frequency of the system is set as 126Hz.
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372 Views