Machine Learning
Seven years of water consumption data, along with population data, were manually collected in collaboration with the local municipality office. This data was then combined with climatic data to model the proposed machine learning algorithm. The weather data was recorded for a period of 7 years using precise meteorological instruments installed in Islamabad at coordinates 33.64° N and 72.98° E, with an elevation of 500 meters above sea level.
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752 Views
We present the RQMD dataset, a comprehensive collection of diverse material samples aimed at advancing computer vision and machine learning algorithms in terrain classification tasks. This dataset contains RGB images of 5 different terrains, such as Asphalt, Brick, Grass, Gravel, and Tiles, captured using an 8-megapixel Raspberry Pi camera from a top-view perspective. Notably, the dataset encompasses images taken at different times of the day, introducing variations in lighting conditions and environmental factors.
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The significance of having sustainable water quality data cannot be overstated. It plays a crucial role in comprehending the historical variations and patterns in river conditions and also helps in understanding how industrial waste impacts the well-being of aquatic ecosystems. To achieve sustainable water management practices, it is imperative to rely on dependable and extensive data. Therefore, accurate monitoring and assessment of various water quality parameters become essential.
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1100 Views
In agriculture, the development of early treatment techniques for plant leaf diseases can be significantly enhanced by employing precise and rapid automatic detection methods. Within this realm of research, two common scenarios encountered in real field cases are the identification of different severity stages of diseases and the detection of multiple pathogens simultaneously affecting a single plant leaf. One major challenge faced in this area is the lack of publicly available datasets that contain images captured under these specific conditions.
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278 Views
We created a 5G dataset by measuring 5G traffic directly from a major mobile operator in South Korea. The model name of the mobile terminal used for traffic measurement is the Samsung Galaxy A90 5G, equipped with a Qualcomm Snapdragon X50 5G modem. We installed PCAPdroid, a packet sniffer software, on the terminal via Google Play. Traffic was measured sequentially per application on two stationary terminals (only one terminal is used for noninteractive services) with no background traffic.
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6487 Views
Lantana flower, originally known as a parasitic and poisonous plant, is expansive to fill many livestock fields. Lantana data sets are open source and can be used by many researchers to create models with higher accuracy. currently the accuracy using this dataset has reached 99.8% using k-NN and preceded by feature extraction using VGG-16 Lantana flower, originally known as a parasitic and poisonous plant, is expansive to fill many livestock fields. Lantana data sets are open source and can be used by many researchers to create models with higher accuracy.
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196 Views
This dataset is a subset from the Oxford University Our World in Data Covid 19 Dataset. This dataset contains data points collected on an ongoing basis from Johns Hopkins University, Center for Systems Science and Engineering COVID-19 data, OXFORD COVID-19 Government Response Tracker, and European Centre for Disease Control, from January 2020 to present.
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169 Views
The morphological characteristics of skeletal muscles, such as fascicle orientation, fascicle length, and muscle thickness, contain valuable mechanical information that aids in understanding muscle contractility and excitation due to commands from the central nervous system. Ultrasound (US) imaging, a non-invasive measurement technique, has been employed in clinical research to provide visualized images that capture morphological characteristics. However, accurately and efficiently detecting the fascicle in US images is challenging.
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201 Views
As a hot research topic, there are many related datasets for occlusion detection. Due to the different scenarios and definitions of occlusion for different tasks, there are significant differences between different occlusion detection datasets, making existing datasets difficult to apply to the video shot occlusion detection task. To this end, we contribute the first large-scale video shot occlusion detection dataset, namely VSOD, which serves as a benchmark for evaluating the performance of shot occlusion detection methods.
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510 Views