Real-time segmentation of weeds in cornfields based on depthwise separable convolution residual network

2020 ◽  
Vol 23 (4) ◽  
pp. 307
Author(s):  
Yinan Lu ◽  
Hao Guo ◽  
Shengsheng Wang
Keyword(s):  
Real Time ◽  
Residual Network ◽  
Time Segmentation

scholarly journals A Residual Network and FPGA Based Real-Time Depth Map Enhancement System

Entropy ◽  
2021 ◽  
Vol 23 (5) ◽  
pp. 546
Author(s):  
Zhenni Li ◽  
Haoyi Sun ◽  
Yuliang Gao ◽  
Jiao Wang
Keyword(s):  
Real Time ◽  
Super Resolution ◽  
Depth Map ◽  
Acquisition System ◽  
Depth Image ◽  
Fpga Design ◽  
Depth Sensing ◽  
Residual Network ◽  
Real Time Processing ◽  
Depth Maps

Depth maps obtained through sensors are often unsatisfactory because of their low-resolution and noise interference. In this paper, we propose a real-time depth map enhancement system based on a residual network which uses dual channels to process depth maps and intensity maps respectively and cancels the preprocessing process, and the algorithm proposed can achieve real-time processing speed at more than 30 fps. Furthermore, the FPGA design and implementation for depth sensing is also introduced. In this FPGA design, intensity image and depth image are captured by the dual-camera synchronous acquisition system as the input of neural network. Experiments on various depth map restoration shows our algorithms has better performance than existing LRMC, DE-CNN and DDTF algorithms on standard datasets and has a better depth map super-resolution, and our FPGA completed the test of the system to ensure that the data throughput of the USB 3.0 interface of the acquisition system is stable at 226 Mbps, and support dual-camera to work at full speed, that is, 54 fps@ (1280 × 960 + 328 × 248 × 3).

scholarly journals Real-Time Segmentation of Non-rigid Surgical Tools Based on Deep Learning and Tracking

2017 ◽  
pp. 84-95 ◽  
Author(s):  
Luis C. García-Peraza-Herrera ◽  
Wenqi Li ◽  
Caspar Gruijthuijsen ◽  
Alain Devreker ◽  
George Attilakos ◽  
...  
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Surgical Tools ◽  
Time Segmentation

Real-Time Segmentation of Surgical Tools and Needle Using a Mobile-U-Net

2021 ◽  
Author(s):  
Jakob Kristian Holm Andersen ◽  
Kim Lindberg Schwaner ◽  
Thiusius Rajeeth Savarimuthu
Keyword(s):  
Real Time ◽  
Surgical Tools ◽  
Time Segmentation

scholarly journals Real-Time Segmentation of Stereo Videos on a Portable System With a Mobile GPU

2012 ◽  
Vol 22 (9) ◽  
pp. 1292-1305 ◽  
Author(s):  
Alexey Abramov ◽  
Karl Pauwels ◽  
Jeremie Papon ◽  
Florentin Worgotter ◽  
Babette Dellen
Keyword(s):  
Real Time ◽  
Mobile Gpu ◽  
Portable System ◽  
Time Segmentation

Real-Time Segmentation of Depth Map Frames on Mobile Devices

2019 ◽  
Author(s):  
Florica Moldoveanu ◽  
Andrei Ciobanu ◽  
Anca Morar ◽  
Alin Moldoveanu ◽  
Victor Asavei
Keyword(s):  
Real Time ◽  
Mobile Devices ◽  
Depth Map ◽  
Time Segmentation

High-density CCD neurocomputer chip for accurate real-time segmentation of noisy images

1991 ◽  
Author(s):  
Michael W. Roth ◽  
K. E. Thompson ◽  
Robert L. Kulp ◽  
E. Brian Alvarez
Keyword(s):  
Real Time ◽  
High Density ◽  
Noisy Images ◽  
Time Segmentation
Sign in / Sign up

Export Citation Format

Share Document