atabak dehban
atabak dehban
Institute for Systems and Robotics (ISR/IST), LARSyS, Instituto Superior Técnico, U. Lisboa
Email confirmado em - Página inicial
Citado por
Citado por
The Impact of Domain Randomization on Object Detection: A Case Study on Parametric Shapes and Synthetic Textures
A Dehban, J Borrego, R Figueiredo, P Moreno, A Bernardino, ...
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2019
Denoising auto-encoders for learning of objects and tools affordances in continuous space
A Dehban, L Jamone, AR Kampff, J Santos-Victor
2016 IEEE International Conference on Robotics and Automation (ICRA), 4866-4871, 2016
A novel approach for optimization in dynamic environments based on modified artificial fish swarm algorithm
D Yazdani, A Sepas-Moghaddam, A Dehban, N Horta
International Journal of Computational Intelligence and Applications 15 (02 …, 2016
Learning at the ends: From hand to tool affordances in humanoid robots
G Saponaro, P Vicente, A Dehban, L Jamone, A Bernardino, ...
2017 Joint IEEE International Conference on Development and Learning and …, 2017
A generic visual perception domain randomisation framework for Gazebo
J Borrego, R Figueiredo, A Dehban, P Moreno, A Bernardino, ...
2018 IEEE International Conference on Autonomous Robot Systems and …, 2018
A robust and efficient framework for fast cylinder detection
R Figueiredo, A Dehban, P Moreno, A Bernardino, J Santos-Victor, ...
Robotics and Autonomous Systems 117, 17-28, 2019
A Deep Probabilistic Framework for Heterogeneous Self-Supervised Learning of Affordances
A Dehban, L Jamone, A Kampff, J Santos-Victor
IEEE RAS International Conference on Humanoid Robots (Humanoids), 2017
Action-conditioned benchmarking of robotic video prediction models: a comparative study
MS Nunes, A Dehban, P Moreno, J Santos-Victor
2020 IEEE International Conference on Robotics and Automation (ICRA), 8316-8322, 2020
Automatic generation of object shapes with desired affordances using voxelgrid representation
M Andries, A Dehban, J Santos-Victor
Frontiers in neurorobotics 14, 22, 2020
A moderately large size dataset to learn visual affordances of objects and tools using icub humanoid robot
A Dehban, L Jamone, AR Kampff, J Santos-Victor
ECCV Workshop on Action and Anticipation for Visual Learning, 2016
Robotic tool use and problem solving based on probabilistic planning and learned affordances
A Antunes, G Saponaro, A Dehban, L Jamone, R Ventura, A Bernardino, ...
IROS Workshop, 2015
A cognitive based driver's steering behavior modeling
A Dehban, A Sajedin, MB Menhaj
2016 4th International Conference on Control, Instrumentation, and …, 2016
Shape-Based Attention for Identification and Localization of Cylindrical Objects
R Figueiredo*, A Dehban*, A Bernardino, J Santos-Victor, H Araújo
IEEE International Conference on Developmental and Learning and on …, 2017
Neuro-ACT cognitive architecture applications in modeling driver’s steering behavior in turns
A Dehban, MB Menhaj, A Sajedin
AUT Journal of Modeling and Simulation 47 (2), 21-29, 2015
Learning deep features for robotic inference from physical interactions
A Dehban, S Zhang, N Cauli, L Jamone, J Santos-Victor
IEEE Transactions on Cognitive and Developmental Systems, 2022
SENSORIMOTOR GRAPH: Action-Conditioned Graph Neural Network for Learning Robotic Soft Hand Dynamics
J Damião Almeida, P Schydlo, A Dehban, J Santos-Victor
arXiv e-prints, arXiv: 2107.08492, 2021
Efficient Resource Allocation for Sparse Multiple Object Tracking
Proceedings of the 12th International Joint Conference on Computer Vision …, 2017
Robotic Interactive Physics Parameters Estimator (RIPPE)
A Dehban*, C Cardoso*, P Vicente, A Bernardino, J Santos-Victor
2019 Joint IEEE 9th International Conference on Development and Learning and …, 2019
3DSGrasp: 3D Shape-Completion for Robotic Grasp
SS Mohammadi, NF Duarte, D Dimou, Y Wang, M Taiana, P Morerio, ...
arXiv preprint arXiv:2301.00866, 2023
Robotic Learning the Sequence of Packing Irregular Objects from Human Demonstrations
A Santos, A Dehban, J Santos-Victor
arXiv preprint arXiv:2210.01645, 2022
O sistema não pode efectuar a operação agora. Tente mais tarde.
Artigos 1–20