On the importance of backbone to the adversarial robustness of object detectors

X Li, H Chen, X Hu - IEEE Transactions on Information …, 2025 - ieeexplore.ieee.org
Object detection is a critical component of various security-sensitive applications, such as
autonomous driving and video surveillance. However, existing object detectors are …

A systematic review of cross-patient approaches for EEG epileptic seizure prediction

S Shafiezadeh, GM Duma, M Pozza… - Journal of Neural …, 2024 - iopscience.iop.org
Objective: Seizure prediction could greatly improve the quality of life of people suffering from
epilepsy. Modern prediction systems leverage artificial intelligence (AI) techniques to …

DHS-DETR: Efficient DETRs with dynamic head switching

H Chen, C Tang, X Hu - Computer Vision and Image Understanding, 2024 - Elsevier
Detection Transformer (DETR) and its variants have emerged a new paradigm to object
detection, but their high computational cost hinders practical applications. By investigating …

Kan-Memvit: A Memory Cached Vision Transformer With Kolmogorov–Arnold Network for Seizure Prediction

H Peng, W Feng, C Nie, H Feng, H Lv, S Wang… - Available at SSRN … - papers.ssrn.com
Automatic seizure prediction is crucial for develo** new therapies for patients with
refractory epilepsy. Throughout the development of deep learning, numerous methods for …

[NAVOD][C] Low-rank sparse representation-based transition subspace learning algorithm for epileptic seizure recognition

H Zang, A Bi, L Zhao, W Ying, J Qian - Journal of Mechanics in …, 2024 - World Scientific
Electroencephalogram (EEG) is a pivotal diagnostic tool for epilepsy. EEG signals have
complex sources, significant individual differences, and data distribution varies across …