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Restoration tasks in low-level vision aim to restore high-quality (HQ) data from their low-quality (LQ) observations. To circumvents the difficulty of acquiring paired data in real scenarios, unpaired ...
Image fusion facilitates the integration of information from various source images of the same scene into a composite image, thereby benefiting perception, analysis, and understanding. Recently, ...
The semiconductor industry is a dynamic landscape of innovation, where new materials, advanced processing techniques, and cutting -edge design converge to shape the future of technology. Powered by ...
Channel Deduction: A New Learning Framework to Acquire Channel From Outdated Samples and Coarse Estimate ...
Obstacle avoidance for uncrewed aerial vehicles (UAVs) in cluttered environments is significantly challenging. Existing obstacle avoidance for UAVs either focuses on fully static environments or ...
What will Wi-Fi 8 be? Driven by the strict requirements of emerging applications, next-generation Wi-Fi is set to prioritize ultra high reliability (UHR) above all. In this article, we explore the ...
Non-Terrestrial Networks (NTN) are expected to be a critical component of 6th Generation (6G) networks, providing ubiquitous, continuous, and scalable services. Satellites emerge as the primary ...
In the remote sensing community, extracting buildings from remote sensing imagery has triggered great interest. While many studies have been conducted, a comprehensive review of these approaches that ...
This article surveys the recent development of semiconductor memory technologies spanning from the mainstream static random-access memory, dynamic random-access memory, and flash memory toward ...
The availability of unprecedented unsupervised training data, along with neural scaling laws, has resulted in an unprecedented surge in model size and compute requirements for serving/training large ...
In this paper, we investigate the design of energy-efficient beamforming for an ISAC system, where the transmitted waveform is optimized for joint multi-user communication and target estimation ...
Over the past decade, domain adaptation has become a widely studied branch of transfer learning which aims to improve performance on target domains by leveraging knowledge from the source domain.
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