Hands on Wheel Classification Based on Depth Images and Neural Networks

This file was created by the TYPO3 extension bib --- Timezone: CEST Creation date: 2020-08-09 Creation time: 10-20-49 --- Number of references 9 inproceedings schmitz2020hands Hands on Wheel Classification Based on Depth Images and Neural Networks 2020 308 06003 MATEC Web of Conferences EDP Sciences 10.1051/matecconf/202030806003 Jan-ChristophSchmitz StephanTilgner KathrinKalischewski DanielWagner AntonKummert inproceedings 8702300 Spoken Letter Recognition using Deep Convolutional Neural Networks on Sparse and Dissimilar Data 2019 1-5 Training;Task analysis;Visualization;Spectrogram;Convolutional neural networks;Image recognition 2019 IEEE International Symposium on Circuits and Systems (ISCAS) 2158-1525 10.1109/ISCAS.2019.8702300 K.Kalischewski D.Wagner J.Velten A.Kummert inproceedings 8702195 Automatic Labeling of Industrial Images by using Generative Adversarial Networks 2019 1-5 Kernel;Generative adversarial networks;Training;Decoding;Generators;Loss measurement;Mutual information 2019 IEEE International Symposium on Circuits and Systems (ISCAS) 2158-1525 10.1109/ISCAS.2019.8702195 D.Wagner K.Kalischewski S.Tilgner J.Velten A.Kummert inproceedings 8702575 Multi-View Fusion Neural Network with Application in the Manufacturing Industry 2019 1-5 Cameras;Cavity resonators;Biological neural networks;Training;Predictive models;Convolutional neural networks 2019 IEEE International Symposium on Circuits and Systems (ISCAS) 2158-1525 10.1109/ISCAS.2019.8702575 S.Tilgner D.Wagner K.Kalischewski J.Velten A.Kummert inproceedings 8070613 Activity recognition for indoor movement and estimation of travelled path 2017 9 1-5 accelerometer data, accelerometers, data analysis, feature extraction, Foot, gyroscopes, human activity detection, human activity recognition, IMU, indoor environment, indoor movement, indoor positioning systems, inertial measurement unit, learning (artificial intelligence), Legged locomotion, machine learning, mobile computing, path estimation, support vector machines, Training, wearable computers, wearables 2017 10th International Workshop on Multidimensional (nD) Systems (nDS) 10.1109/nds.2017.8070613 KathrinKalischewski DanielWagner J<prt>ö</prt>rgVelten AntonKummert inproceedings velten2017nds Examination of direct form vs. WDF realization of a 2-D quadrantal fan filter in FPGA hardware 2017 9 Multidimensional (nD) Systems (nDS), 2017 10th International Workshop on 10.1109/NDS.2017.8070614 J<prt>ö</prt>rgVelten DanielWagner LechKolonko KathrinKalischewski StephanTilgner TimSchwerdtfeger AntonKummert inproceedings Wagner2017 Activity recognition using inertial sensors and a 2-D convolutional neural network 2017 9 1-6 Multidimensional (nD) Systems (nDS), 2017 10th International Workshop on 10.1109/NDS.2017.8070615 DanielWagner KathrinKalischewski J<prt>ö</prt>rgVelten AntonKummert inproceedings kalischewski15nds Orientation and Positioning with Inertial Sensors for walking frame guidance 2015 9 78 - 82

Vila Real, Portugal

of the 9th International Workshop on Multidimensional (nD) Systems (nDS'15) KathrinKalischewski DanielWagner J<prt>ö</prt>rgVelten AntonKummert inproceedings wagner15nds Detection of ascending and descending stairways by surface normal vectors 2015 9 83 - 86

Vila Real, Portugal

of the 9th International Workshop on Multidimensional (nD) Systems (nDS'15) DanielWagner KathrinKalischewski J<prt>ö</prt>rgVelten AntonKummert