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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

Harnessing the Synergy between Pushing, Grasping, and Throwing to Enhance Object Manipulation in Cluttered Scenarios

Identification and Copy Number Variant Analysis of Enhancer Regions of Genes Causing Spinocerebellar Ataxia

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

Lifelong Robot Library Learning: Bootstrapping Composable and Generalizable Skills for Embodied Control with Language Models

Self-supervised Learning for Joint Pushing and Grasping Policies in Highly Cluttered Environments

TiV-ODE: A Neural ODE-based Approach for Controllable Video Generation from Text-Image Pairs

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

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