Machine Learning
This dataset has 32,000 remote sensing images in UAV scenes of tiny objects with labels.
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325 Views
Indoor location-based services have high requirements for positioning accuracy. Fingerprint positioning methods are popular, where Received Signal Strength (RSS) of WiFi is widely used because of its availability. Our dataset is from the dataset provided in the literature [1]. The WiFi measurements were collected in an area among the bookshelves in a wing of a university’s library building. The collection process was finished with a Samsung Galaxy S3 smartphone and software explicitly developed, and a total of 448 Access Points (APs) were detected during the experiment.
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157 Views
This robust dataset is extracted from the International Skin Imaging Collaboration (ISIC). Similar datasets are used for the annual ISIC Challenge, presenting an opportunity for the computer science community to produce algorithms that can outperform professional dermatology. The submitted dataset contains approximately 1,000 images of malignant melanomas, as well as approximately 1,000 images of benign melanomas.
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3100 Views
This Data set was obtained from a Hospital in Karaikudi, Tamilnadu Iindia, and has 400 insstances with 25 attributes, intended for classification problems.
The Data Set has medical relevant variables that can be associated to the presence of CKD (Chronical Kidney Diasease). Some of the variables can be arguably more relevant for the model, and after analysis some of them can be correlated, so it's recommended to analyze the dataset and decide the best approach based on individual needs.
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4333 Views
Microwave active antenna sensor based MDBM meter is developed for continuous glucose measurement in human body. MDBM meter consists of Antiallergic Abdominal belt with radar IC (RCWL0516) mixer IC (BFR520) and HSIS antenna sensor. Microwave active antenna sensor is H-shaped patch with I-shaped slot, which is placed on human pancreas and acquires reflected microwave signals from dielectric materials in pancreas. Pancreas dielectric materials radiation property changes during insulin secretion.
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152 Views
This dataset consists of “.csv” files of 4 different routing attacks (Blackhole Attack, Flooding Attack, DODAG Version Number Attack, and Decreased Rank Attack) targeting the RPL protocol, and these files are taken from Cooja (Contiki network simulator). It allows researchers to develop IDS for RPL-based IoT networks using Artificial Intelligence and Machine Learning methods without simulating attacks. Simulating these attacks by mimicking real-world attack scenarios is essential to developing and testing protection mechanisms against such attacks.
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3564 Views
Unmanned aerial vehicles (UAVs) are being used for various applications, but the associated cyber risks are also increasing. Machine learning techniques have been successfully adopted to develop intrusion detection systems (IDSs). However, none of the existing works published the cyber or physical datasets that have been used to develop the IDS, which hinders further research in this field.
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2849 Views
The extended bandit learning game algorithm can search the best solution for the hybrid discrete-continuous strategy space. At each learning time, the player can quickly decide based on a finite discrete strategy pool, thereby improving the learning efficiency.
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41 Views
The dataset contains a collection of V2X (Vehicle-to-Everything) messages for classification, prioritization, and spam message detection. It comprises 1,000 messages with varying message types, content, priorities, and spam labels. The messages are sourced from different vehicles with specific destination vehicles or broadcast to all vehicles. They cover various message types, including traffic updates, emergency alerts, weather notifications, hazard warnings, roadwork information, and spam messages. The priority of the messages is categorized as either high, medium, or low.
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1181 Views
The rapid growth of interconnected IoT devices has introduced complexities in their monitoring and management. Autonomous and intelligent management systems are essential for addressing these challenges and achieving self-healing, self-configuring, and self-managing networks. Intelligent agents have emerged as a powerful solution for autonomous network design, but their dynamic and intelligent management requires processing large volumes of data for training network function agents.
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79 Views