Cybersecurity has always been the focus of Internet research. Malware refers to software intentionally designed to harm computer systems, networks, ...
A physics-constrained AI model called VLSet-AE automates feature extraction from DRIE cross-sections with 96 percent accuracy ...
Sub-headline: BIT researchers introduce Malcom to tackle cross-domain encrypted traffic detection using self-supervised ...
Abstract: Lying at the intersection of self-supervised learning (SSL) and knowledge distillation (KD), Self-supervised KD (SSKD) differs from classical KD frameworks by assuming the teacher model is ...
Abstract: This article presents a deep autoencoder-based methodology for unsupervised anomaly detection in centrifugal pumps under limited failure data conditions, focusing on real-world applications ...
SenseTime's SenseNova team released U1 on April 28, 2026 - a family of multimodal models built on a rethought architecture ...
This repository implements an end-to-end anomaly detection pipeline for autonomous system sensor streams using an LSTM autoencoder. The model learns to reconstruct ...
Synthetic Aperture Radar (SAR) imagery plays a critical role in all-weather, day-and-night remote sensing applications. However, existing SAR-oriented deep learning is constrained by data scarcity, ...
Tiny etched structures sit at the heart of many modern sensors and microsystems, but judging whether those structures were ...
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