An Effective Method for Minimizing Domain Gap in Sim2Real Object Recognition Using Domain Randomization
نویسندگان
چکیده
منابع مشابه
Cross-Domain Object Recognition Using Object Alignment
One popular solution to the problem of cross-domain object recognition is minimizing the difference between source and target distributions. Existing methods are devoted to minimizing that domain difference in a complex image space, which makes the problem hard to solve because of background influence. To discount the influence, we propose to minimize that difference using object alignment. We ...
متن کاملseismic texture recognition in time-frequency domain
in seismic exploration studies different types of techniques are used to recognize seismic features in terms of their temporal and spatial spectra. variations in frequency content are sensitive to subtle changes in reflection information (castro de matos et al., 2003). in this study the joint time-frequency analysis is used for seismic texture recognition. discrete wavelet transform (dwt) witho...
متن کاملDomain Adaptive Neural Networks for Object Recognition
We propose a simple neural network model to deal with the domain adaptation problem in object recognition. Our model incorporates the Maximum Mean Discrepancy (MMD) measure as a regularization in the supervised learning to reduce the distribution mismatch between the source and target domains in the latent space. From experiments, we demonstrate that the MMD regularization is an effective tool ...
متن کاملObject Recognition Using Frequency Domain Blur Invariant Features
In this paper, we propose novel blur invariant features for the recognition of objects in images. The features are computed either using the phase-only spectrum or bispectrum of the images and are invariant to centrally symmetric blur, such as linear motion or defocus blur as well as linear illumination changes. The features based on the bispectrum are also invariant to translation, and accordi...
متن کاملThe method of gap domain wall fermions
I present the gap domain wall fermion (GDWF) method. I show that GDWF induce a substantial gap in the transfer matrix Hamiltonian along the fifth dimension. As a result they significantly improve the chiral properties of domain wall fermions in the large to intermediate lattice spacing regime of QCD, 1 to 2 GeV. Furthermore, I argue that this method should also improve the chiral properties of ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Proceedings of International Conference on Artificial Life and Robotics
سال: 2023
ISSN: ['2188-7829', '2435-9157']
DOI: https://doi.org/10.5954/icarob.2023.os17-6