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: In this article, input-to-state stability (ISS) and stabilization are examined for sampled-data systems under deterministic aperiodic sampling and random sampling, respectively. Using the ...

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 ...

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

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 ...

Random sampling analysis method, vector illustration example... Random sampling analysis method, vector illustration example diagram. Unbiased choosing people sample from the crowd. Population ...

Random sampling is a powerful technique used to analyze data effectively by selecting a representative sample from a larger dataset. Excel provides various ways to generate random samples, making it ...