Search Results for author:
Found 9 papers, 4 papers with code
MIXAD: Memory-Induced Explainable Time Series Anomaly Detection
Addressing this gap, we introduce MIXAD (Memory-Induced Explainable Time Series Anomaly Detection), a model designed for interpretable anomaly detection.
SSMT: Few-Shot Traffic Forecasting with Single Source Meta-Transfer
Specifically, we use memory-augmented attention to store the heterogeneous spatial knowledge from the source city and selectively recall them for the data-scarce target city.
GDFlow: Anomaly Detection with NCDE-based Normalizing Flow for Advanced Driver Assistance System
For electric vehicles, the Adaptive Cruise Control (ACC) in Advanced Driver Assistance Systems (ADAS) is designed to assist braking based on driving conditions, road inclines, predefined deceleration strengths, and user braking patterns.
Mechanical compression regulates tumor spheroid invasion into a 3D collagen matrix
Although the effects of tension within 3D extracellular matrices on tumor growth and invasion are well established, the role of compression in tumor mechanics and invasion is largely unexplored.
VFP290K: A Large-Scale Benchmark Dataset for Vision-based Fallen Person Detection
Accordingly, detection of these anomalous events is of paramount importance for a number of applications, including but not limited to CCTV surveillance, security, and health care.
Ranked #1 on
Anomaly Detection In Surveillance Videos
on VFP290K
Evaluation of an Audio-Video Multimodal Deepfake Dataset using Unimodal and Multimodal Detectors
On the other hand, to develop a good deepfake detector that can cope with the recent advancements in deepfake generation, we need to have a detector that can detect deepfakes of multiple modalities, i. e., videos and audios.
FakeAVCeleb: A Novel Audio-Video Multimodal Deepfake Dataset
We generate this dataset using the most popular deepfake generation methods.
CoReD: Generalizing Fake Media Detection with Continual Representation using Distillation
Over the last few decades, artificial intelligence research has made tremendous strides, but it still heavily relies on fixed datasets in stationary environments.
FReTAL: Generalizing Deepfake Detection using Knowledge Distillation and Representation Learning
We use FReTAL to perform domain adaptation tasks on new deepfake datasets while minimizing catastrophic forgetting.
