Machine Learning
The deployment of unmanned aerial vehicles (UAV) for logistics and other civil purposes is consistently disrupting airspace security. Consequently, there is a scarcity of robust datasets for the development of real-time systems that can checkmate the incessant deployment of UAVs in carrying out criminal or terrorist activities. VisioDECT is a robust vision-based drone dataset for classifying, detecting, and countering unauthorized drone deployment using visual and electro-optical infra-red detection technologies.
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7523 Views
In order to contribute to the development of automatic methods for the detection of bacilli, TBimages is an image dataset composed of two subsets: TbImages_SS1 contains 10 images per field, of different focal depths, and aims to support the definition of autofocus metrics and also the development of extended focus imaging methods to facilitate the detection of bacilli in smear microscopy imaging. TbImages_SS2 aims to support the development of automatic bacilli detection.
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Five users aged 23, 25, 31, 42, and 46 participated in the experiment. The users sat comfortably in a chair. A green LED of 1 cm diameter was placed at a distance of about 1 meter from a person's eyes. EEG signals were recorded using g.USBAmp with 16 active electrodes. The users were stimulated with flickering LED lights with frequencies: 5 Hz, 6 Hz, 7 Hz, and 8 Hz. The stimulation lasted 30 seconds. The recorded signals were divided into the data used for training, the first 20 seconds, and the data used for testing, the next 10 seconds, for each signal.
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724 Views
For the purpose of experimentation, the historical stock prices of three petroleum companies: Pakistan State Oil (PSO), Hascol, and Attock Petroleum Limited (APL), are extracted from the Pakistan Stock Exchange (PSX) website through a web scrapper for the last four years. Different attributes related to the stocks of each of these companies are extracted for each day. Along with this, for each of these companies, Twitter data for sentiment analysis is also extracted using Twint.
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666 Views
In this study, we present advances on the development of proactive control for online individual user adaptation in a welfare robot guidance scenario, with the integration of three main modules: navigation control, visual human detection, and temporal error correlation-based neural learning. The proposed control approach can drive a mobile robot to autonomously navigate in relevant indoor environments. At the same time, it can predict human walking speed based on visual information without prior knowledge of personality and preferences (i.e., walking speed).
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234 Views
A mobile sensor can be described as a kind of smart technology that can capture minor or major changes in an environment and can respond by performing a particular task. The scope of the dataset is for forensic purposes that will help segregate day-to-day activities from criminal actions. Smartphones supplied with sensors can be utilised for monitoring and recording simple daily activities such as walking, climbing stairs, eating and more. For the generation of this dataset, we have collected data for 13 classes of daily life activities, which has been done by a single individual.
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296 Views
Using Python. we crawl a total of 18, 793 diabetes related Q&A between Jun. 1, 2016 and Sept. 1, 2020 on xywy.com, a famous Chinese Online Medical Community. Each data contains four parts of the question detail page: Title, Problem Description, User ID and Question Time, and three parts of the doctor’s answer page: Doctor ID, Answer Content and Answer Time. After preprocessing such as cleaning and deduplication, we finally obtain 18,521 valid data.
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16 Views
Datsets and scripts are for derivation of a lightweight AIoT malware detection model.
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433 Views
SART contains 3000 tweets labelled with respect to the polarity of the sentiment expressed: positive, negative or neutral. Each class contains 1300 tweets and the dataset is split into train/validation/test csv files.
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24 Views
This dataset provides Channel Impulse Response (CIR) measurements from standard-compliant IEEE 802.11ay packets to validate Integrated Sensing and Communication (ISAC) methods. The CIR sequences contain reflections of the transmitted packets on people moving in an indoor environment. They are collected with a 60 GHz software-defined radio experimentation platform based on the IEEE 802.11ay Wi-Fi standard, which is not affected by frequency offsets by operating in full-duplex mode.
The dataset is divided into two parts:
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1841 Views