5 papers · 1 filter
MIXAD: Memory-Induced Explainable Time Series Anomaly Detection
Minha Kim, Kishor Kumar Bhaumik, Amin Ahsan Ali +1
For modern industrial applications, accurately detecting and diagnosing anomalies in multivariate time series data is essential. Despite such need, most state-of-the-art methods of…
SSMT: Few-Shot Traffic Forecasting with Single Source Meta-Transfer
Kishor Kumar Bhaumik, Minha Kim, Fahim Faisal Niloy +2
Traffic forecasting in Intelligent Transportation Systems (ITS) is vital for intelligent traffic prediction. Yet, ITS often relies on data from traffic sensors or vehicle devices,…
Disrupting Diffusion-based Inpainters with Semantic Digression
Geonho Son, Juhun Lee, Simon S. Woo
The fabrication of visual misinformation on the web and social media has increased exponentially with the advent of foundational text-to-image diffusion models. Namely, Stable Diff…
Continuous Memory Representation for Anomaly Detection
Joo Chan Lee, Taejune Kim, Eunbyung Park +2
There have been significant advancements in anomaly detection in an unsupervised manner, where only normal images are available for training. Several recent methods aim to detect a…
Source-Free Online Domain Adaptive Semantic Segmentation of Satellite Images under Image Degradation
Fahim Faisal Niloy, Kishor Kumar Bhaumik, Simon S. Woo
Online adaptation to distribution shifts in satellite image segmentation stands as a crucial yet underexplored problem. In this paper, we address source-free and online domain adap…