Artificial Intelligence
In precision agriculture, detecting productive crop fields is an essential practice that allows the farmer to evaluate operating performance separately and compare different seed varieties, pesticides, and fertilizers. However, manually identifying productive fields is often time-consuming, costly, and subjective. Previous studies explore different methods to detect crop fields using advanced machine learning algorithms to support the specialists’ decisions, but they often lack good quality labeled data.
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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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196 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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503 Views
This dataset is made for traditional, machine learning, and deep neural-network-based virtual sensor development and evaluation.
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Forum-java is a log dataset that we collected in an open source java-based web forum system {https://github.com/Qbian61/forum-java.}. It is a Java-based forum platform developed by a technology company and widely used for social media and programming technique sharing it contains abundant and diverse functions, like posting articles, creating FAQs, etc., which can satisfy most of the requirements of users.
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43 Views
The risks to children of online predators in real time gaming environments have been an area of growing concern. Research towards the development of near real time capabilities has been the focus of most queries published in this area of study. In this paper, we present Protectbot, a comprehensive safety framework used to interact with users in online gaming chat rooms. Protectbot employs a variant of the GPT-2 model known as DialoGPT, a generative pre-trained transformer designed specifically for conversation.
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551 Views
This Named Entities dataset is implemented by employing the widely used Large Language Model (LLM), BERT, on the CORD-19 biomedical literature corpus. By fine-tuning the pre-trained BERT on the CORD-NER dataset, the model gains the ability to comprehend the context and semantics of biomedical named entities. The refined model is then utilized on the CORD-19 to extract more contextually relevant and updated named entities. However, fine-tuning large datasets with LLMs poses a challenge. To counter this, two distinct sampling methodologies are utilized.
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299 Views
<p> The dataset is digital health data. It contains heart rate data extracted from Fitbit version 2 smartwatch worn by a healthy male Asian person of 48 years old. Data is of one-month duration. We have uploaded a zip file that contains data from different days. Data for each day has a separate file. The file name contains the date. Each file is in csv format. Each file has two columns – timestamp and heart rate. It is a continuous time-series heart rate data. Heart rate was recorded seamlessly at 5 sec interval. However, there may be missing datum.
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