IEEE

Dynamic Manipulation of Deformable Objects using Imitation Learning with Adaptation to Hardware Constraints

Abstract: Imitation Learning (IL) is a promising paradigm for learning dynamic manipulation of deformable objects since it does not depend on difficult-to-create accurate simulations of such objects.
GitHub

ContrasTR: Contrastive Learning for Multi-Object Tracking with Transformers

TL;DR: We show how object detection models can be turned into multi-object tracking models with almost no overhead. We also introduce a pre-training scheme on detection that improves tracking without ...
GitHub

MP2CDLO: Self-supervised Learning of Reconstructing Deformable Linear Objects under Single-Frame Occluded View

Create conda environments and active it. conda create -n MP2CDLO python=3.9 conda activate MP2CDLO Install torch1.13.0+cu117. pip install torch==1.13.0+cu117 ...
IEEE

Utilization of Remote Sensing Dataset and a Deep Learning Object Detection Model to Map Siam Weed Infestations

Abstract: Remote sensing data are valuable for detecting, mapping, and managing invasive weed species. This article introduces an innovative algorithm for mapping Siam weed infestations using a ...