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Conjecturing-Based Computational Discovery of Patterns in Data
J.P.Brooks, D.J.Edwards, C.E.Larson....
Published date-11/23/2020
Modern machine learning methods are designed to exploit complex patterns in data regardless of their form, while not necessarily revealing them to the investigator. Here we demonstrate situations where modern …
An analysis of Reinforcement Learning applied to Coach task in IEEE Very Small Size Soccer
CarlosH.C.Pena, MateusG.Machado, MarianaS.Barros....
Published date-11/23/2020
The IEEE Very Small Size Soccer (VSSS) is a robot soccer competition in which two teams of three small robots play against each other. Traditionally, a deterministic coach agent will …
End-to-End Framework for Efficient Deep Learning Using Metasurfaces Optics
CarlosMauricioVillegasBurgos, TianqiYang, NickVamivakas....
Published date-11/23/2020
Deep learning using Convolutional Neural Networks (CNNs) has been shown to significantly out-performed many conventional vision algorithms. Despite efforts to increase the CNN efficiency both algorithmically and with specialized hardware, …
Structure-Aware Completion of Photogrammetric Meshes in Urban Road Environment
QingZhu, QishenShang, HanHu....
Published date-11/23/2020
ObjectDetection
Photogrammetric mesh models obtained from aerial oblique images have been widely used for urban reconstruction. However, the photogrammetric meshes also suffer from severe texture problems, especially on the road areas …
condLSTM-Q: A novel deep learning model for predicting Covid-19 mortality in fine geographical Scale
HyeongChanJo, JuhyunKim, Tzu-ChenHuang....
Published date-11/23/2020
Predictive models with a focus on different spatial-temporal scales benefit governments and healthcare systems to combat the COVID-19 pandemic. Here we present the conditional Long Short-Term Memory networks with Quantile …
Reachable Polyhedral Marching (RPM): A Safety Verification Algorithm for Robotic Systems with Deep Neural Network Components
JosephA.Vincent, MacSchwager....
Published date-11/23/2020
We present a method for computing exact reachable sets for deep neural networks with rectified linear unit (ReLU) activation. Our method is well-suited for use in rigorous safety analysis of …