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Found 7 papers, 0 papers with code
Show and Grasp: Few-shot Semantic Segmentation for Robot Grasping through Zero-shot Foundation Models
The ability of a robot to pick an object, known as robot grasping, is crucial for several applications, such as assembly or sorting.
Comparisons among different stochastic selection of activation layers for convolutional neural networks for healthcare
In this paper we classify biomedical images using ensembles of neural networks.
Robotic Arm Control and Task Training through Deep Reinforcement Learning
This paper proposes a detailed and extensive comparison of the Trust Region Policy Optimization and DeepQ-Network with Normalized Advantage Functions with respect to other state of the art algorithms, namely Deep Deterministic Policy Gradient and Vanilla Policy Gradient.
Real-time Tracking-by-Detection of Human Motion in RGB-D Camera Networks
This paper presents a novel real-time tracking system capable of improving body pose estimation algorithms in distributed camera networks.
Ensemble of Convolutional Neural Networks Trained with Different Activation Functions
The goal of this work is to propose an ensemble of Convolutional Neural Networks trained using several different activation functions.
Ensemble of Deep Learned Features for Melanoma Classification
The aim of this work is to propose an ensemble of descriptors for Melanoma Classification, whose performance has been evaluated on validation and test datasets of the melanoma challenge 2018.
