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GitHub - stefan-ainetter/grasp_det_seg_cnn: Code for ICRA21 paper End-to-end Trainable Deep Neural Network for Robotic Grasp Detection and Semantic Segmentation from RGB.
Convolutional multi-grasp detection using grasp path for RGBD images - ScienceDirect
UESTC RGB-D Dataset
Computer Science authors/titles new
Frontiers Fast Location and Recognition of Green Apple Based on RGB-D Image
Sensors, Free Full-Text
Experimental setup: operator (left) & robots (right)
Attack visualization for GR-ConvNet-RGB-D on Cornell grasp dataset. The
Autonomous Vehicles Enabled by the Integration of IoT, Edge Intelligence, 5G, and Blockchain. - Abstract - Europe PMC
Convolutional multi-grasp detection using grasp path for RGBD images - ScienceDirect
Nak CHONG, Professor (Full), Doctor of Philosophy, Japan Advanced Institute of Science and Technology, Komatsu, School of Information Science
Attack visualization for GR-ConvNet-RGB-D on OCID grasp dataset. The
On the Analyses of Medical Images Using Traditional Machine Learning Techniques and Convolutional Neural Networks
Autonomous Vehicles Enabled by the Integration of IoT, Edge Intelligence, 5G, and Blockchain. - Abstract - Europe PMC
ERCIM News 114 - Human Robot Interaction by Peter Kunz - Issuu