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Vision-based robotic gras** from object localization, object pose estimation to grasp estimation for parallel grippers: a review
This paper presents a comprehensive survey on vision-based robotic gras**. We
conclude three key tasks during vision-based robotic gras**, which are object localization …
conclude three key tasks during vision-based robotic gras**, which are object localization …
An Overview of Deep Neural Networks for Few-Shot Learning
J Zhao, L Kong, J Lv - Big Data Mining and Analytics, 2024 - ieeexplore.ieee.org
Recent advancements in deep learning have led to significant breakthroughs across various
fields. However, these methods often require extensive labeled data for optimal …
fields. However, these methods often require extensive labeled data for optimal …
Unseen object few-shot semantic segmentation for robotic gras**
X Liu, Y Zhang, D Shan - IEEE Robotics and Automation …, 2022 - ieeexplore.ieee.org
Semantic segmentation is a popular technology enabling robots to perceive and interact
with the environment sufficiently. However, unseen objects in the new environment make it …
with the environment sufficiently. However, unseen objects in the new environment make it …
Generative robotic gras** using depthwise separable convolution
Y Teng, P Gao - Computers & Electrical Engineering, 2021 - Elsevier
In this paper, we present an end-to-end approach method using deep learning for grasp
detection. Our method is a real-time processing method for discrete depth image sampling …
detection. Our method is a real-time processing method for discrete depth image sampling …
A practical multi-stage grasp detection method for kinova robot in stacked environments
X Dong, Y Jiang, F Zhao, J ** attempts, attributable to factors including object …
Annotation Cost Reduction of Stream-based Active Learning by Automated Weak Labeling using a Robot Arm
K Suzuki, T Sunagawa, T Sasaki… - 2021 IEEE/RSJ …, 2021 - ieeexplore.ieee.org
Stream-based active learning (AL) is an efficient training data collection method, and it is
used to reduce human annotation cost required in machine learning. However, it is difficult …
used to reduce human annotation cost required in machine learning. However, it is difficult …