In this study, semantic segmentation approaches based on convolutional neuronal network (CNN) were performed to enhance the crawling waves differentiation.
In this regard, the purpose of this work is to employ semantic segmentation approaches, U- net and DeepLabV3, to enhance the differentiation of CW and compare ...
In this study, semantic segmentation approaches based on convolutional neuronal network (CNN) were performed to enhance the crawling waves differentiation.
This method estimates tissue elasticity by analyzing the speed of shear waves captured by an ultrasonic Doppler transducer, and offers several advantages such ...
It becomes evident that the buildings class is better generalized using DeepLab, confirming the findings of Section 5.2, since to a smaller part than U-Net, ...
Comparison between U-Net and DeepLabV3 for Crawling Waves Sonoelastography approach. A Caytano, S Merino, H Trujillo, B Castaneda, SE Romero. 2023 19th ...
The results show that U-net has a higher mIoU value than Deeplab V3 but has less processing time and the number of parameters.
Missing: Crawling Waves Sonoelastography
Exploring fusion techniques in U-Net and DeepLab V3 architectures ...
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Two well-known network architectures, U-Net and DeepLab V3+, developed originally for RGB image data, are modified to accept additional input channels, ...
Comparison between U-Net and DeepLabV3 for Crawling Waves. Sonoelastography approach. Presenter: Alexys Ramiro Caytano. Modified Continuous Wavelet Transform ...
Effects of aberration in crawling wave sonoelastography · Gabriela ... Comparison between U-Net and DeepLabV3 for Crawling Waves Sonoelastography approach.