Artificial Intelligence
Human intention is an internal, mental characterization for acquiring desired information. From
interactive interfaces, containing either textual or graphical information, intention to perceive desired
information is subjective and strongly connected with eye gaze. In this work, we determine such intention by
analyzing real-time eye gaze data with a low-cost regular webcam. We extracted unique features (e.g.,
Fixation Count, Eye Movement Ratio) from the eye gaze data of 31 participants to generate the dataset
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This dataset is a Verilog-a implementation of a dynamic compact model of ferroelectric capacitance. It can be run with a SPICE-type circuit simulator.
Researchers using this dataset should cite it as follows: Ning Feng, Hao Li, Chang Su, Lining Zhang, Qianqian Huang,Runsheng Wang, and Ru Huang, A Dynamic Compact Model for Ferroelectric Capacitance, IEEE Electron Device Letters, DOI: 10.1109/LED.2022.3141413
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The data collection of the human subjects' brainwaves was performed using a specific experiment of showing a set of pictures that stimulate different emotions on the human subjects. In order to create this kind of experiment, a Java application is developed by us to simulate the visual experiment with the IAPS. It is a simple Java application developed in Eclipse IDE. The main purpose of the application is to collect subjects' credential information and show in sequence the selected set of images from IAPS.
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We have long known that the characterization of protein three-dimensional structure is key to obtaining a detailed understanding of protein function. Computational approaches to protein structure characterization have largely addressed a narrow formulation of the problem, where the goal is the determination of one structure, also known as the native structure, from a given protein amino-acid sequence. However, many researchers over the years have argued for broadening our view of proteins to account for the multiplicity of native structures.
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NLOS/LOS acoustic signal dataset, including 4 rooms, 12,800 data, labeled as NLOS and LOS.
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The dataset provides textures generated from elliptical cosine and sinc fractional Brownian field models.
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This dataset is composed by both real and sythetic images of power transmission lines, which can be fed to deep neural networks training and applied to line's inspection task. The images are divided into three distinct classes, representing power lines with different geometric properties. The real world acquired images were labeled as "circuito_real" (real circuit), while the synthetic ones were identified as "circuito_simples" (simple circuit) or "circuito_duplo" (double circuit). There are 348 total images for each class, 232 inteded for training and 116 aimed for validation/testing.
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The code and dataset for multimodal unknown surface material classification.
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The crime rate is increasing at a high rate in India. Terrorist attacks like Mumbai 26/11, Pulwama attack, Pune German Beckary attacks have created terrific fear amongst Indian Society. Video analytics plays a significant role in detecting and predicting such suspicious human activities using deep learning models It will help in reducing the increasing crime rate by preventing treacherous actions. Video analytics analyzes the video content and adds brains to eyes i.e. analytics to the camera. It extracts contents from the video by monitoring the video in real-time.
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