#Calibration

7 статей
Основы Universal Measurement and Calibration Protocol (XCP) Хабр
Хабр

Основы Universal Measurement and Calibration Protocol (XCP)

XCP (Universal Measurement and Calibration Protocol) — это бинарный автомобильный интерфейсно-независимый протокол прикладного уровня модели OSI-7. Используется при разработке и отладке ECU. Появился ...

Хабр
arXiv Computer Vision
arXiv Computer Vision

A Calibration Audit of Confidence in Feed-Forward 3D Reconstruction

arXiv:2608.29705v1 Announce Type: new Abstract: Feed-forward 3D reconstruction models emit a per-pixel confidence that downstream systems read as a reliability signal. It is trained as a loss weight, ...

arXiv Computer Vision
arXiv AI
arXiv AI

SPECTRA: Subspace-Preserving Embedding Calibration, Transport, and Replay for Fully Few-Shot Class-Incremental Audio Classification

arXiv:2608.25054v1 Полная классификация класса с несколькими выстрелами (FFCAC) требует распознавания новых звуковых классов только из нескольких помеченных примеров за сессию, не забывая ранее изучен...

arXiv AI
arXiv Machine Learning
arXiv Machine Learning

Dynamic Regime-Aware Conformal Calibration for Reliable Economic Forecast Intervals under Multiple Distribution Shifts

arXiv:2608.17079v1 Announce Type: new Abstract: Conformal prediction provides distribution-free prediction intervals but relies on exchangeability, an assumption often violated in economic forecasting...

arXiv Machine Learning
arXiv Statistics
arXiv Statistics

Multi-Level Bayesian Calibration of a Multi-Component Dynamic System Model

arXiv:2608.18430v1 Announce Type: cross Abstract: This paper proposes a multi-level Bayesian calibration approach that fuses information from heterogeneous sources and accounts for uncertainties in mo...

arXiv Statistics
arXiv Computer Vision
arXiv Computer Vision

Zero-MELO: Test-Time Evidence Calibration with Multimodal LLMs for Zero-Shot Micro-Gesture Recognition

arXiv:2608.14854v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) excel in general video understanding, their capability in fine-grained and motion-centric tasks remains l...

arXiv Computer Vision