artificial intelligence
Bananas are widely farmed and consumed, offering essential nutrients like manganese, vitamin B6, vitamin C, and magnesium. They come in various breeds with distinct visual traits, including size, shape, color, texture, and skin patterns. To classify these varieties, five deep learning models—VGG16, ResNet50, MobileNet, Inception-v3, and a customized CNN—were trained on banana images. These models enhance quality control and supply chain management by accurately identifying banana breeds.
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129 Views
Legal analysis utilizing natural language processing and machine learning technologies is a difficult undertaking that has recently sparked the interest of many academics and industries. Using a human-annotated dataset summarized into colloquial Thai from Supreme Court decisions, this work investigates a different combination of NLP, ML, and rule-based techniques for accurate legal case analysis as per Thai law, especially property-related offences, with the intuition to imitate the lawyer's cognitive process.
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21 Views
This dataset contains human motion data collected using inertial measurement units (IMUs), including accelerometer and gyroscope readings, from participants performing specific activities. The data was gathered under controlled conditions with verbal informed consent and includes diverse motion patterns that can be used for research in human activity recognition, wearable sensor applications, and machine learning algorithm development. Each sample is labeled and processed to ensure consistency, with raw and augmented data available for use.
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68 Views
This is a dataset that contains the testing results presented in the manuscript "Exploring the Potential of Offline LLMs in Data Science: A Study on Code Generation for Data Analysis", and it aims to assess offline LLMs' capabilities in code generation for data analytics tasks. Best utilization of the dataset would occur after thorough understanding of the manuscript. A total of 250 testing results were generated for each of the two LLMs evaluated. They were merged, leading to the creation of this current dataset.
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45 Views
This dataset supports a systematic review on the integration of Digital Twins (DT), Extended Reality (XR), and Artificial Intelligence (AI) in Reconfigurable Manufacturing Systems (RMS). The data was collected during a search performed on March 3, 2024, using the Scopus database. Articles published since 2018 were screened based on predefined inclusion and exclusion criteria, resulting in 37 articles selected for qualitative analysis.
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119 Views
Please cite the following paper when using this dataset:
Vanessa Su and Nirmalya Thakur, “COVID-19 on YouTube: A Data-Driven Analysis of Sentiment, Toxicity, and Content Recommendations”, Proceedings of the IEEE 15th Annual Computing and Communication Workshop and Conference 2025, Las Vegas, USA, Jan 06-08, 2025 (Paper accepted for publication, Preprint: https://arxiv.org/abs/2412.17180).
Abstract:
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146 Views
C-SRR Radiation Patterns. The pixels from the radiation pattern generated by positioning the C-SRR over the phantom model with and without cancerous tissue were extracted using various window shapes and sizes to form the dataset. For this, pixel sampling operations such as average, minimum, maximum, and median are performed. Pixel reconfiguration to triangle, square, symmetric and asymmetric is also performed. In average pixel sampling, the average value of the pixel color is divided by the total number of pixels.
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158 Views
The increasing prevalence of encrypted traffic in
modern networks poses significant challenges for network security,
particularly in detecting and classifying malicious activities
and application signatures. To overcome this issue, deep learning
has turned out to be a promising candidate owing to its ability
to learn complex data patterns. In this work, we present a
deep learning-based novel and robust framework for encrypted
traffic analysis (ETA) which leverages the power of Bidirectional
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209 Views
To provide a standardized approach for testing and benchmarking secure evaluation of transformer-based models, we developed the iDASH24 Homomorphic Encryption track dataset. This dataset is centered on protein sequence classification as the benchmark task. It includes a neural network model with a transformer architecture and a sample dataset, both used to build and evaluate secure evaluation strategies.
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190 Views
Endemic fish species are key components in seafood culinary excursions. Despite the increasing interest in leveraging technology to enhance various seafood culinary activities, there is a shortage of comprehensive datasets containing images of seafood used in artificial intelligence research, mainly those showcasing endemic fish. This research endeavors to bridge this gap by increasing the accuracy of fish recognition and introducing a new dataset comprising images of native fish for application in various machine-learning investigations.
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188 Views