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Over ons Praktische zaken Waar vindt u ons S.H. (Hamidreza) Mohades Kasaei, PhD

Speerpunten

My research interest lies at the intersection of machine learning, robotics, and machine vision, particularly, at the area of open-ended learning3D object perceptiongrasp affordance detection, and object manipulation. I am interested in developing algorithms for an adaptive perception system based on interactive environment exploration and open-ended learning, which enables robots to learn from past experiences and interact with human users. I have been investigating on active perception, where robots use their mobility and manipulation capabilities not only to gain perceptual information to model the world but also to predict the next-best-view for improving object detection and manipulation performances. I have evaluated my works on different robotic platforms, including PR2, robotic arms (UR5e, Kinova, Franka), and humanoid robots. For more details, please check my webpage  www.ai.rug.nl/hkasaei

Publicaties

Lifelong ensemble learning based on multiple representations for few-shot object recognition

Early or Late Fusion Matters: Efficient RGB-D Fusion in Vision Transformers for 3D Object Recognition

Enhancing Fine-Grained 3D Object Recognition Using Hybrid Multi-Modal Vision Transformer-CNN Models

Explain What You See: Open-Ended Segmentation and Recognition of Occluded 3D Objects

Frontier Semantic Exploration for Visual Target Navigation

Instance-wise Grasp Synthesis for Robotic Grasping

L3MVN: Leveraging Large Language Models for Visual Target Navigation

MORE: simultaneous multi-view 3D object recognition and pose estimation

MVGrasp: Real-time multi-view 3D object grasping in highly cluttered environments

A Hybrid Compositional Reasoning Approach for Interactive Robot Manipulation

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