Abstract: Label assignment is a crucial process in object detection, which significantly influences the detection performance by determining positive or negative samples during training process.

Abstract: This paper proposes a new perspective on the relationship between the sampling and aliasing. Unlike the uniform sampling case, where the aliases are simply periodic replicas of the original ...

Investopedia contributors come from a range of backgrounds, and over 25 years there have been thousands of expert writers and editors who have contributed. Thomas J. Brock is a CFA and CPA with more ...

This important study shows a surprising scale-invariance of the covariance spectrum of large-scale recordings in the zebrafish brain in vivo. A convincing analysis demonstrates that a Euclidean random ...

Introduction: Species distribution models can predict the spatial distribution of vector-borne diseases by forming associations between known vector distribution and environmental variables. In ...

R package for statistical modeling with the Skellam distribution, supporting inference, random sampling, and regression for differences of independent Poisson counts.

Sampling from probability distributions with known density functions (up to normalization) is a fundamental challenge across various scientific domains. From Bayesian uncertainty quantification to ...

Denoising Diffusion Probabilistic Models (DDPMs) have gained great attention in adversarial purification. Current diffusion-based works focus on designing effective condition-guided mechanisms while ...

Quantum computers are a revolutionary technology that harnesses the principles of quantum mechanics to perform calculations that would be infeasible for classical computers. Evaluating the performance ...