Artificial Intelligence
A dataset comprising 500 data points was gathered by collecting answers to 250 computer science problems assigned in classes and quizzes from students. To generate this dataset, a response was selected from a random student for each question. The same questions were then asked to ChatGPT 3.0, and the answers were recorded. Based on the source of the response (either student or GPT), the dataset was labeled accordingly. The resulting labeled dataset includes the list of assignment and quiz questions, along with the corresponding answers from students and ChatGPT.
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2584 Views
Accurate recognition of targets in the orchard environment is the key to vision perception for picking robots. Factors such as small, densely growing plum fruit targets and high occlusion lead to unsatisfactory recognition of plum fruit by vision algorithms. Therefore, this paper proposes an improved YOLOv5s model to detect highly occluded and dense plums in orchards. First, the backbone network of YOLOv5s is improved in this paper.
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30 Views
CAPTCHA (Completely Automated Public Turing Tests to Tell Computers and Humans Apart). Only humans can successfully complete this test; current computer systems cannot. It is utilized in several applications for both human and machine identification. Text-based CAPTCHAs are the most typical type used on websites. Most of the letters in this protected CAPTCHA script are in English, it is challenging for rural residents who only speak their native tongues to pass the test.
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1466 Views
Please cite the following paper when using this dataset:
N. Thakur, K. Khanna, S. Cui, N. Azizi, and Z. Liu, “Mining and Analysis of Search Interests related to Online Learning Platforms from Different Countries since the Beginning of COVID-19” [Unpublished Paper - Paper submitted to HCI International 2023, Copenhagen, Denmark, 23-28 July 2023]
Brief Description of Dataset file - Interest_Dataset.csv:
Attribute Name: Week
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239 Views
Please cite the following paper when using this dataset:
N. Thakur, K. Khanna, S. Cui, N. Azizi, and Z. Liu, “Mining and Analysis of Search Interests related to Online Learning Platforms from Different Countries since the Beginning of COVID-19” [Unpublished Paper - Paper submitted to HCI International 2023, Copenhagen, Denmark, 23-28 July 2023]
Brief Description of Dataset file - Interest_Dataset.csv:
Attribute Name: Week
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Views
Please cite the following paper when using this dataset:
N. Thakur, K. Khanna, S. Cui, N. Azizi, and Z. Liu, “Mining and Analysis of Search Interests related to Online Learning Platforms from Different Countries since the Beginning of COVID-19”, Proceedings of the 25th International Conference on Human-Computer Interaction (HCII 2023), Copenhagen, Denmark, July 23-28, 2023 (Accepted for Publication)
Brief Description of Dataset file - Interest_Dataset.csv:
Attribute Name: Week
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1258 Views
Please cite the following paper when using this dataset:
N. Thakur, K. Khanna, S. Cui, N. Azizi, and Z. Liu, “Mining and Analysis of Search Interests related to Online Learning Platforms from Different Countries since the Beginning of COVID-19” [Unpublished Paper - Paper submitted to HCI International 2023, Copenhagen, Denmark, 23-28 July 2023]
Brief Description of Dataset file - Interest_Dataset.csv:
Attribute Name: Week
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15 Views
We present a new dataset with the target of advancing the scene parsing task from images to videos. Our dataset aims to perform Video Scene Parsing in the Wild (VSPW), which covers a wide range of real-world scenarios and categories. To be specific, our VSPW is featured from the following aspects: 1) Well-trimmed longtemporal clips. Each video contains a complete shot, lasting around 5 seconds on average. 2) Dense annotation. The pixel-level annotations are provided at a high frame rate of 15 f/s. 3) High resolution.
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85 Views
Development of the Complex-Valued (CV) deep learning architectures has enabled us to exploit the amplitude and phase components of the CV Synthetic Aperture Radar (SAR) data. However, most of the available annotated SAR datasets provide only the amplitude information (Only detected SAR data) and disregard the phase information. The lack of high-quality and large-scale annotated CV-SAR datasets is a significant challenge for developing CV deep learning algorithms in remote sensing.
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1706 Views
Passive missiles, such as short-range or within-visual-range air-to-air missiles (SRAAMs or WVRAAMs) and man-portable air defense systems (MANPADS), which do not emit radio frequencies (RF) and thus evade detection by an aircraft’s Radar Warning Receiver (RWR). Current passive missile detection systems, primarily relying on Midwave Infrared (MWIR) exhibit limitations regarding high false alarm rates and extensive processing requirements.
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62 Views