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Multi-object tracking is a crucial task in intelligent surveillance, yet it remains challenging in crowded environments due to severe occlusion, perspective distortion, and appearance similarity. To a
Multi-modal 3D object detection has exhibited significant progress in recent years. However, most existing methods can hardly scale to long-range scenarios due to their reliance on dense 3D features,
When a system operates under impulsive disturbances and conventional state estimation methods become ineffective, robust peak error reduction is required. In this paper, the error-to-error transfer fu
Private Hash Matching (PHM) enables the detection of harmful media in end-to-end encrypted communication by comparing user media hashes against a server-side set of known harmful hashes, without expos
Deep learning-based side-channel attack (DLSCA) has become the dominant paradigm for extracting sensitive information from hardware implementations due to its ability to learn discriminative features
The aim of a backdoor attack is to manipulate the behavior of a DNN under trigger-activated conditions by poisoning the dataset. Most backdoor detectors can be regarded as feature clustering methods a
Deep neural networks (DNNs) are vulnerable to backdoor/Trojan attacks, posing a severe threat to security-critical applications. In this paper, we investigate a scenario in which two different backdoo
Wax-mediated surface layers introduce anisotropic diffusion and non-Lambertian reflectance that distort observable pest morphology in agricultural imagery, degrading the reliability of data-driven det
Standard CMOS imagers provide reliable real-time imaging only above 1 lx, typical of daylight. Electron Bombarded Active Pixel Sensor (EBAPS), employing photoelectron bombardment gain, delivers clear
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The IEEE Signal Processing Society is dedicated to supporting the professional growth and career advancement of its members in the dynamic field of signal processing. Learn More
Signal processing education and professional development program for all career levels. Learn more.