Learning to Segment Generic Handheld Objects Using Class-Agnostic Deep Comparison and Segmentation Network
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DOI: 10.1109/lra.2018.2856917
Abstract: Learning unknown objects in the environment is important for detection and manipulation tasks. Prior to learning the unknown objects the ground-truth labels have to be provided. The data annotation or labeling can be achieved in… read more here.
Keywords: network; handheld objects; deep comparison; class agnostic ... See more keywords
Deep Comparison Convolutional Neural Network for Industrial Localization
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Automation Science and Engineering"
DOI: 10.1109/tase.2025.3548279
Abstract: Accurate visual localization is essential for industrial applications, e.g., automated workpiece localization and manipulation. Traditional template matching methods are limited by lighting conditions and lack kinematic flexibility, while Convolutional Neural Network (CNN)-based approaches necessitate retraining… read more here.
Keywords: deep comparison; convolutional neural; neural network; localization ... See more keywords