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GitHub8d

Center-aware Residual Anomaly Synthesis for Multi-class Industrial Anomaly Detection

This repository contains source code for CRAS implemented with PyTorch. CRAS aims to address inter-class interference and intra-class overlap in multi-class anomaly detection through center-aware ...
IEEE20d

CLIP-FSQAE: Clip-Guided Finite Scalar Quantized Autoencoder for Few-Shot Anomaly Detection

Abstract: Industrial anomaly detection is hindered by data inefficiency and dependence on large-scale training sets. We introduce CLIP-FSQAE, a novel framework for few-shot anomaly detection that ...
Frontiers23d

Improved injury detection through harmonizing multi-site neuroimaging data after experimental TBI: a Translational Outcomes Project in Neurotrauma consortium study

Multi-site neuroimaging studies have become increasingly common in order to generate larger samples of reproducible data to answer questions associated with smaller effect sizes. The data ...
C&EN24d

Data-Driven Flow Control for Natural Gas Pipeline Networks: Optimizing via Anomaly Detection and Residual Weight Coefficients

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. The natural gas pipeline network has a complex topology with variable flow directions, ...
GitHub28d

PhD Dissertation: Label Blindness in Unlabeled Out-of-Distribution Detection

This repository contains the LaTeX source code for my PhD dissertation, which includes the integration of my ICLR 2025 paper "Can We Ignore Labels in Out-of-Distribution Detection?" as Chapter 4. The ...
IEEE1mon

Self-Supervised Learning Meets Custom Autoencoder Classifier: A Semi-Supervised Approach for Encrypted Traffic Anomaly Detection

Abstract: The widespread adoption of encryption in computer networks has made detecting malicious traffic, especially at network perimeters, increasingly challenging. As packet contents are concealed, ...