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Ji-hwan Kim, Dong-seok Lee and Soon-kak Kwon
This paper proposes a method to classify food types and to estimate meal intake amounts in pre- and post-meal images through a deep learning object detection network. The food types and the food regions are detected through Mask R-CNN. In order to make b...
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Ka Seng Chou, Teng Lai Wong, Kei Long Wong, Lu Shen, Davide Aguiari, Rita Tse, Su-Kit Tang and Giovanni Pau
This research addresses the challenges of visually impaired individuals? independent travel by avoiding obstacles. The study proposes a distance estimation method for uncontrolled three-dimensional environments to aid navigation towards labeled target ob...
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Egor I. Chetkin, Sergei L. Shishkin and Bogdan L. Kozyrskiy
Bayesian neural networks (BNNs) are effective tools for a variety of tasks that allow for the estimation of the uncertainty of the model. As BNNs use prior constraints on parameters, they are better regularized and less prone to overfitting, which is a s...
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Bakht Zaman, Dusica Marijan and Tetyana Kholodna
The availability of automatic identification system (AIS) data for tracking vessels has paved the way for improvements in maritime safety and efficiency. However, one of the main challenges in using AIS data is often the low quality of the data. Practica...
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Chunhyun Paik, Yongjoo Chung and Young Jin Kim
The estimation of power curve is the central task for efficient operation and prediction of wind power generation. It is often the case, however, that the actual data exhibit a great deal of variations in power output with respect to wind speed, and thus...
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