CIFAR-10

CIFAR-10 is a dataset containing 60,000 32x32 color images in 10 different classes, commonly used to evaluate the performance of machine learning models in image classification tasks.

Papers using CIFAR-10 (6)

ART For Diffusion Sampling: A Reinforcement Learning Approach To Timestep Schedule2026The M-factor: A Novel Metric for Evaluating Neural Architecture Search in Resource-Constrained Environments2025The Tsetlin Machine Goes Deep: Logical Learning and Reasoning With Graphs2025Toward Lifelong Learning in Equilibrium Propagation: Sleep-like and Awake Rehearsal for Enhanced Stability2025ART for Diffusion Sampling: A Reinforcement Learning Approach to Timestep Schedule2026Quantum Reinforcement Learning-Guided Diffusion Model for Image Synthesis via Hybrid Quantum-Classical Generative Model Architectures2025