Image Semantic Segmentation Method Based on Atrous Algorithm and Convolution CRF

Lv, Linjue; Li, Xingwei; Jin, Jiating; Li, Xinlong

doi:10.1109/iccsnt47585.2019.8962446

Cited by 5 publications

(1 citation statement)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…At present, there is no systematic mathematical theoretical basis for SPP structure, but the setting of atrous value and the number of convolution kernels are the key factors to determine the performance of SPP, therefore, this paper will optimize the model from these two aspects. After summarizing the relevant references [10][11][12][13][14][15], it is found that the current research has personalized and transformed the atrous value and the number of convolution kernels for their respective fields, so as to improve the matching degree between the model and the application field. After specific analysis, the following principles are summarized:…”

Section: Improvement Of Model Structurementioning

confidence: 99%

Robot Three-Finger Grasping Strategy Based on DeeplabV3+

Bai

Yang

et al. 2021

Actuators

View full text Add to dashboard Cite

Researchers all over the world are aiming to make robots with accurate and stable human-like grasp capabilities, which will expand the application field of robots, and development of a reasonable grasping strategy is the premise of this function. In this paper, the improved deeplabV3+ semantic segmentation algorithm is used to predict a triangle grasp strategy. The improved model was trained on the relabeled Cornell grasp datasets and tested on self-collected datasets. Compared with the existing rectangular grasp strategy, the proposed algorithm and triangle grasp strategy have achieved outstanding performance in stability, accuracy, and speed. Finally, based on the ROS platform, this paper deploys the trained model and verifies the real effect of the trained grasping strategy prediction model, and achieves excellent grasping effect.

show abstract