Researchers have developed a dynamic range compression dual-domain attention network for enhancing tunnel images under extreme exposure conditions, a problem that continues to challenge transportation ...

Seismic inversion is vital for reservoir characterization but faces significant challenges in complex fluvial-deltaic systems due to strong heterogeneity and thin-bedded formations. Current methods, ...

To address the issues of low accuracy, high dependence on prior knowledge, and poor adaptability in fusing multi-channel features in existing plunger pump fault diagnosis methods, a new method based ...

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ABSTRACT: Purpose: To introduce a practical method of using an Electron Density Phantom (EDP) to evaluate different dose calculation algorithms for photon beams in a treatment planning system (TPS) ...

A new brain-inspired AI method called Lp-Convolution enhances image recognition by dynamically reshaping CNN filters, combining biological realism with improved performance and efficiency. Credit: ...

A team of researchers from the Institute for Basic Science, Yonsei University, and the Max Planck Institute have developed a new artificial intelligence (AI) technique that brings machine vision ...

Large Language Models (LLMs) significantly benefit from attention mechanisms, enabling the effective retrieval of contextual information. Nevertheless, traditional attention methods primarily depend ...

Convolution is used in a variety of signal-processing applications, including time-domain-waveform filtering. In a recent series on the inverse fast Fourier transform (FFT), we concluded with a ...

Event-based cameras are bio-inspired vision sensors that mimic the sparse and asynchronous activation of the animal retina, offering advantages such as low latency and low computational load in ...