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Compositional Zero-Shot Learning (CZSL) aims to recognize novel compositions using knowledge learned from seen attribute-object compositions in the training set. Previous works mainly project an image ...
In this paper, we study the application of Vehicle-to-Everything (V2X) communication to improve the perception performance of autonomous vehicles. We present V2X-ViTs, a robust cooperative perception ...
In high-resolution ADCs, mismatch and gain errors are the main bottlenecks when aiming to achieve lower distortion and noise floor. Various techniques have been proposed to address these issues.
True digital orthophoto maps (DOMs) are vital spatial data sources due to their high precision, detail, and accessibility. However, traditional generation methods using image differential correction ...
Existing human visual perception-oriented image compression methods well maintain the perceptual quality of compressed images, but they may introduce fake details into the compressed images, and ...
Synthetic aperture radar (SAR) image target detection and recognition (SAR-TDR) tasks have become research hot spots in the remote sensing application. These targets include ships, vehicles, aircraft, ...
As Metaverse emerges as the next-generation Internet paradigm, the ability to efficiently generate content is paramount. AI-Generated Content (AIGC) emerges as a key solution, yet the ...
Feature drift is caused by the dynamic coupling of target features and degradation factors, which reduce underwater detector performance. We redefine feature drift as the instability of target ...
Recently, artificial intelligence and machine learning in general have demonstrated remarkable performances in many tasks, from image processing to natural language processing, especially with the ...
Grid-forming (GFM) inverters are recognized as a viable solution to increase the penetration of renewable energy in bulk power systems. However, they are physically different from synchronous ...
High-density surface electromyography (EMG) decomposition provides a valuable non-invasive approach to accessing key motor unit information for a range of applications. This communication summarizes ...
Early and accurate detection of network intrusions is crucial to ensure network security and stability. Existing network intrusion detection methods mainly use conventional machine learning or deep ...