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Classification of Factual and Non-Factual Statements Using Adversarially Trained LSTM Networks
(2020-06-08)
Being able to determine which statements are factual and therefore likely candidates for further verification is a key value-add in any automated fact-checking system. For this task, it has been shown that LSTMs outperform ...
GENERATING ADVERSARIAL EXAMPLES FOR RECRUITMENT RANKING ALGORITHMS
(2020-12-16)
There is no doubt that recruitment process plays an important role for both employers and applicants. Based on huge number of job candidates and open vacancies, recruitment process is expensive, time consuming and stressful ...
Randomized and Evolutionary Approaches to Dataset Characterization, Feature Weighting, and Sampling in K-Nearest Neighbors
(2020-06-05)
K-Nearest Neighbors (KNN) has remained one of the most popular methods for supervised machine learning tasks. However, its performance often depends on the characteristics of the dataset and on appropriate feature scaling. ...
PERSON IDENTIFICATION AND TINETTI SCORE ASSESSMENT USING BALANCE PARAMETERS TO DETERMINE FALL RISK
(2020-09-03)
This thesis is aimed at a substantial health problem among the elderly population that is “Fall”, a major cause of accidental home deaths. Studies show approximately one-third of community-dwelling people over 65 years of ...
In Situ Sensor Calibration Using Noise Consistency
(2020-09-08)
Robots rely on sensors to map their surroundings. As a result, the accuracy of the map depends heavily on the sensor noise and in particular on accurate knowledge of it. The common way to ...
SEMI-AUTOMATIC HAND POSE ESTIMATION USING A SINGLE DEPTH CAMERA
(2020-11-30)
This paper addresses the problem of 3D hand pose annotations using a single depth camera. Although hand pose estimation methods rely critically on accurate 3D training data, creating such reliable training data is challenging ...