Machine Learning
This dataset consists of high-resolution visible-spectrum (RGB) and thermal infrared (TIR) images of two vineyards (Vitis vinifera L.) with varieties of Mouhtaro and Merlot, which was captured by Unmanned Aerial Vehicle (UAV) carrying TIR and RGB sensors three times in a cultivation period.
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SCD Dataset: This new dataset has been specifically created for the development and education of children with down syndrome. The dataset, containing a total of 13,500 Turkish question-answer pairs, has "positive" and "negative" emotion labels. In the context of human-robot interaction, accurately identifying and addressing positive and negative emotions has a significant impact on user experience and satisfaction. Neutral questions and answers provide less information in terms of sentiment analysis and are less relevant to the purpose of this study.
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Dataset: IQ samples of LTE, 5G NR, WiFi, ITS-G5, and C-V2X PC5
Thes dataset comprises IQ samples captured from ITSG-5, C-V2X PC5, WiFi, LTE, 5G NR and Noise. Six different dataset bunches are collected at sampling rates of 1, 5, 10, 15 , 20, and 25 Msps. In each dataset cluster, 7500 examples are collected from each considered technology. The dataset size at each considered sampling rate is 7500 X M, where M can be 44, 220, 440, 660, 880, and 1100 for a sampling rate of 1, 5, 10, 15 , 20, and 25 Msps,respectively.
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Dataset for Identification of Saturated and Unsaturated WiFi Networks
The Dataset comprises the histogram of Inter-frame spacing for saturated and unsaturated WiFi networks.
In order to develop a CNN model that can classify saturated and unsaturated traffic in WiFi network, we prepared a large dataset that represents the traffic characteristics of both cases.
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Dataset for Identification of Saturated and Unsaturated WiFi Networks
The Dataset comprises the histogram of Inter-frame spacing for saturated and unsaturated WiFi networks.
In order to develop a CNN model that can classify saturated and unsaturated traffic in WiFi network, we prepared a large dataset that represents the traffic characteristics of both cases.
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This dataset was initially collected by Mrs Athira P K with the help of teachers and students of Rahmania school for handicapped, Kozhikode, Kerala, India. Later the dataset was extended by many other BTech and MTech students with the help of their friends.
MUDRA NITC dataset consists of videos of static and dynamic gestures of Indian sign language. In static gestures mainly static alphabets videos and preprocessed image frames are included.
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To illustrate the impact of the obstacles, we consider indoor and outdoor scenarios. We consider the Department of Computer Science and Engineering, IIT(BHU) buildings as indoor buildings and the railway platform as an outdoor scenario. Here, we use single-channel LG in our experiment. The distance between LNs and LG varies from 5 to 50 meters. The floor map illustrates the walls, doors, and windows between LNs and LG. We consider railway stations for the outdoor environment. The outdoor environment did not consist of obstacles between LNs and LG.
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The concept of wellness, as proposed by Halbert L. Dunn, recognizes the importance of multiple dimensions, such as social and mental well-being, in maintaining overall health. Neglecting these dimensions can have long-term negative consequences on an individual's mental well-being. In the context of traditional in-person therapy sessions, efforts are made to manually identify underlying factors that contribute to mental disturbances, as these factors, if triggered, can potentially lead to severe mental health disorders.
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