Comparative Analysis of OOD Detection Methods Using Deep Learning on Benchmark Datasets

5 Aug 2024

This section presents an evaluation of the proposed OOD detection method using benchmark datasets MNIST and CIFAR10, as well as the GTSRB industrial dataset.

Advancing OOD Detection: A Deep Learning Approach

5 Aug 2024

This paper proposes a novel framework for out-of-distribution (OOD) data detection, combining deep learning with statistical measures.

Rethinking OOD Detection: Combining Autoencoders with Cutting-Edge Techniques

5 Aug 2024

This section outlines a new methodology for out-of-distribution (OOD) detection using deep autoencoders for feature learning and dimensionality reduction

Exploring Statistical Methods for OOD Detection: KD, MD, kNN, and LOF

5 Aug 2024

This section provides an in-depth look at various statistical measures for out-of-distribution (OOD) detection

Quality Assurance of a GPT-Based Sentiment Analysis System

5 Aug 2024

Explore advanced methods for detecting out-of-distribution (OOD) data in AI quality management (AIQM).

Recommendations for Verifying HDR Subjective Testing Workflows: Abstract and Introduction

7 Jul 2024

In this paper, researchers present a set of recommendations for conformance testing of High Dynamic Range displays and content.

Recommendations for Verifying HDR Subjective Testing Workflows: HDR Subjective Testing Workflow

7 Jul 2024

In this paper, researchers present a set of recommendations for conformance testing of High Dynamic Range displays and content.

Recommendations for Verifying HDR Subjective Testing Workflows: Conclusion

7 Jul 2024

In this paper, researchers present a set of recommendations for conformance testing of High Dynamic Range displays and content.

Recommendations for Verifying HDR Subjective Testing Workflows: HDR Standards

7 Jul 2024

In this paper, researchers present a set of recommendations for conformance testing of High Dynamic Range displays and content.