Istraživanje mogućnosti semantičke segmentacije slika sa IoT uređaja
DOI:
https://doi.org/10.24867/14BE23ZivkovicKljučne reči:
Semantička segmentacija, ERFNet, Unet, IoT uređaji, ESP-32 CamApstrakt
U ovom radu je razvijen IoT sistem za akviziciju slike korišćenjem ESP32-Cam modula i implementirane su ERFNet i Unet arhitekture konvolucionih neuronskih mreža. Mreže su obučavane na Cityscapes i Camvid bazama slika i poređene su njihove performanse na slikama dobijenim sa IoT uređaja i DSLR fotoaparata kao i na test slikama iz skupova na kojima su obučavane.
Reference
[1] Romera, E., Alvarez, J. M., Bergasa, L. M., & Arroyo, R. (2017). Erfnet: Efficient residual factorized convnet for real-time semantic segmentation. IEEE Transactions on Intelligent Transportation Systems, 19(1), 263-272.
[2] Kaiming He, Xiangyu Zhang, Shaoqing Ren, & Jian Sun. (2015). Deep Residual Learning for Image Recognition..
[3] Ronneberger, O. (2015, May 18). U-Net: Convolutional Networks for Biomedical Image Segmentation.
[4] M. Cordts, M. Omran, S. Ramos, T. Rehfeld, M. Enzweiler, R. Benenson, U. Franke, S. Roth, and B. Schiele, “The Cityscapes Dataset for Semantic Urban Scene Understanding,” in Proc. of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016
[5] Julien Fauqueur, Gabriel Brostow, Roberto Cipolla, Assisted Video Object Labeling By Joint Tracking of Regions and Keypoints, IEEE International Conference on Computer Vision (ICCV'2007) Interactive Computer Vision Workshop. Rio de Janeiro, Brazil, October 2007
[6] https://github.com/baudcode/tf-semantic-segmentation
[7] Z. C. Lipton, C. Elkan, & B. Narayanaswamy. (2014). Thresholding Classifiers to Maximize F1 Score.
[8] Ha. Rezatofighi, N. Tsoi, J. Gwak, A. Sadeghian, I. Reid, & S. Savarese. (2019). Generalized Intersection over Union: A Metric and A Loss for Bounding Box
[2] Kaiming He, Xiangyu Zhang, Shaoqing Ren, & Jian Sun. (2015). Deep Residual Learning for Image Recognition..
[3] Ronneberger, O. (2015, May 18). U-Net: Convolutional Networks for Biomedical Image Segmentation.
[4] M. Cordts, M. Omran, S. Ramos, T. Rehfeld, M. Enzweiler, R. Benenson, U. Franke, S. Roth, and B. Schiele, “The Cityscapes Dataset for Semantic Urban Scene Understanding,” in Proc. of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016
[5] Julien Fauqueur, Gabriel Brostow, Roberto Cipolla, Assisted Video Object Labeling By Joint Tracking of Regions and Keypoints, IEEE International Conference on Computer Vision (ICCV'2007) Interactive Computer Vision Workshop. Rio de Janeiro, Brazil, October 2007
[6] https://github.com/baudcode/tf-semantic-segmentation
[7] Z. C. Lipton, C. Elkan, & B. Narayanaswamy. (2014). Thresholding Classifiers to Maximize F1 Score.
[8] Ha. Rezatofighi, N. Tsoi, J. Gwak, A. Sadeghian, I. Reid, & S. Savarese. (2019). Generalized Intersection over Union: A Metric and A Loss for Bounding Box
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Objavljeno
2021-09-09
Broj časopisa
Rubrika
Elektrotehničko i računarsko inženjerstvo
