Machine Learning
This experiment was implemented to collect infrared images of the coal and gangue samples at the temperature of 323.15 K. Additionally, it showed that distinguishing between coal and gangue samples is feasible, although the area, thickness, and surface conditions were changed at a constant temperature during the process of capturing the infrared images. The coal and gangue were randomly collected from the same mine. The random samples had different weights, shapes, areas, thicknesses, and surface conations.
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834 Views
The Dravidian Spam SMS dataset has Spam and Ham messages in English, Tamil, Telugu, Kannada, and Malayalam languages. Nearly 7700 messages were collected by sending friends and other contacts a Google form. Language experts (reading and writing skills) were used to label the messages of corresponding languages carefully. The dataset also includes the Tamil verbatim messages written in English. For example, “Nee Nalama”. The Ham messages are mostly normal. Spam messages include business, annoying, and unnecessary messages an anonymous user sends.
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600 Views
The Customer log dataset is a 12.5 GB JSON file and it contains 18 columns and 26,259,199 records. There are 12 string columns and 6 numeric columns, which may also contain null or NaN values. The columns include userId, artist, auth, firstName, gender, itemInSession, lastName, length, level, location, method, page, registration, sessionId, song,status, ts and userAgent.
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1356 Views
The FMK (Finger Major Knuckle) dataset was proposed and created to support the experiments of identity verificatio of knuckles of middle and thumb fingers modalites. The images of this dataset were captured using the rear camera of an OPPO A12 smartphone. This dataset was created from 20 different subjects between the ages of 30 and 67. For each subject there are 3 images of major knuckle for the middle finger and 3 images of major knuckle for thumb finger.. The FMK dataset was proposed and constructed for testing and evaluation.
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476 Views
Abstract—This paper presents a novel approach to optimizing resource allocation in Internet of Things (IoT) networks, focusing on enhancing energy efficiency (EE) while maintaining age of information (AoI) awareness through device-to-device (D2D) communication. Our proposed solution integrates simultaneous wireless information and power transfer (SWIPT) with energy harvesting (EH) techniques. Specifically, D2D users employ time switching (TS) to harvest energy from the environment, while IoT users utilize power splitting (PS) to obtain energy from base stations (BS).
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755 Views
This dataset contains full details of the use case scenarios. Those can be used for effort elicitation using the adapted Use Case Points method. Despite the extensive use of UCP in software engineering, it has yet to be adapted for IoT systems, which is essential for project management and resource planning. Our proposed adaptation, UCP for IoT, is based on a four-layer IoT architecture and tailors the standard software UCP to the specifications of IoT systems.
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166 Views
The dataset is named Chinese rose disease dataset, including healthy leaves, black spot leaves, powdery mildew leaves and downy mildew leaves. All images in this dataset were collected from Nanyang City, Henan Province, China. And all images were collected under natural conditions in order to ensure the true execution of the images. To improve the image variety, we randomly enhance the images in the dataset by flipped, changed the brightness, added Salt and pepper noise and added Gaussian noise.
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892 Views
This dataset has 32,000 remote sensing images in UAV scenes of tiny objects with labels.
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330 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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162 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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3218 Views