然而，随着人工智能模型的规模不断扩张，单纯依靠简单直接「堆参数、堆数据」提升性能的模式正逐渐遇到瓶颈。面对大模型训练代价高昂、性能增长趋缓等挑战，学术界和产业界亟需新的网络架构创新。 近日，范鹤鹤（浙江大学）、杨易（浙江大学）、Mohan ...

Abstract: Obtaining high signal-to-noise ratio (SNR) data is significant for the subsequent processing and interpretation of seismic data. In recent years, the convolutional neural network (CNN) has ...

Months of effort by Sean Combs & his team to secure a presidential pardon from Donald Trump have apparently come up short due ...

Abstract: Surface defect detection is very important for the printed circuit board (PCB) to ensure their quality requirements. This article proposes a reliable and lightweight adaptive convolution ...

Today Danny unboxes the T238 V2 Large Capacity Grenade Toy with Time-delayed Function for Gel Ball BBs Airsoft Wargame - Grey ...

Native Instruments has officially unveiled Odes, the third chapter in its acclaimed Evolution series, following the beloved ...

WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, today announced that active exploration is underway in the ...

Simple quantum-classical neural networks achieve good results in classifying lesions with fewer computational parameters. Scientists from São Paulo State University demonstrated a hybrid model at an ...

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A windowed sinc function can implement a low-pass filter, and a two-dimensional convolutional filter can blur or sharpen images. In part 3 of this series, we introduced a low-pass filter based on the ...

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 ...