Artificial Intelligence

This project investigates bias in automatic facial recognition (FR). Specifically, subjects are grouped into predefined subgroups based on gender, ethnicity, and age. We propose a novel image collection called Balanced Faces in the Wild (BFW), which is balanced across eight subgroups (i.e., 800 face images of 100 subjects, each with 25 face samples).

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The goal of our research is to identify malicious advertisement URLs and to apply adversarial attack on ensembles. We extract lexical and web-scrapped features from using python code. And then 4 machine learning algorithms are applied for the classification process and then used the K-Means clustering for the visual understanding. We check the vulnerability of the models by the adversarial examples. We applied Zeroth Order Optimization adversarial attack on the models and compute the attack accuracy.

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This dataset contains 1050 multi-pattern multi-bin wafer bin maps (WBMs) synthesized from WM-811K binary WBM dataset and real world multi-bin WBMs using a trained pix2pix model.

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The Baseline set described in the submitted IEEE article  as Baseline_set  contains 1442450 rows, where the number of rows varied between 15395 and 197542 for the 16 subjects;  the average per subject being 69095 rows. The data set is filtered and standardized as described in III.C in the submission . The other data sets used in the article are derived from Baseline set.

The data set in .csv format contains the columns timestamp, user_id, session_id, acc_var, hr, rmssd, sdnn, st, eda, eda_freq, bm, location, and concentration. The time step is 5 seconds.

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One to three columns of data are X, Y, Z coordinates respectively

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One to three columns of data are X, Y and Z coordinates respectively.

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Mindlin Plate data used for training DNN surrogate model for Uncertainty Quantification.

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This dataset has received power measurements from three receivers using a mobile transmitter. An area of 4m x 2m was divided into 200 squares. The transmitter was positioned in each grid and 100 measurements of RSSI values received at three fixed receivers were made, as shown in the graph. This dataset has a total of 2000 rows corresponding to 100 examples in each of the 200 grid positions. In addition, the dataset has the following columns:

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Computer vision can be used by robotic leg prostheses and exoskeletons to improve high-level transitions between different locomotion modes (e.g., level-ground walking to stair ascent) through the prediction of future environmental states. Here we developed the StairNet dataset to support research and development in vision-based automated stair recognition.

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Retail Gaze, a dataset for remote gaze estimation in real-world retail environments. Retail Gaze is composed of 3,922 images of individuals looking at products in a retail environment, with 12 camera capture angles.Each image captures the third-person view of the customer and shelves. Location of the gaze point, the Bounding box of the person's head, segmentation masks of the gazed at product areas are provided as annotations.

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