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On the importance of backbone to the adversarial robustness of object detectors
Object detection is a critical component of various security-sensitive applications, such as
autonomous driving and video surveillance. However, existing object detectors are …
autonomous driving and video surveillance. However, existing object detectors are …
A systematic review of cross-patient approaches for EEG epileptic seizure prediction
Objective: Seizure prediction could greatly improve the quality of life of people suffering from
epilepsy. Modern prediction systems leverage artificial intelligence (AI) techniques to …
epilepsy. Modern prediction systems leverage artificial intelligence (AI) techniques to …
DHS-DETR: Efficient DETRs with dynamic head switching
Detection Transformer (DETR) and its variants have emerged a new paradigm to object
detection, but their high computational cost hinders practical applications. By investigating …
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 …
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 …
complex sources, significant individual differences, and data distribution varies across …