#convolution 검색 결과

A #convolution to the assembly An insanity to the genius A blot to the brightness A balance to the quiver A hinderance to the continuance A treasure to the lacking A difference to the apathy An eeriness, a uniqueness An anomaly, a weirdness; A rarity, an oddness #vss365

Folabz_'s tweet image. A #convolution
to the assembly

An insanity
to the genius

A blot
to the brightness

A balance
to the quiver

A hinderance
to the continuance

A treasure
to the lacking

A difference
to the apathy

An eeriness,
a uniqueness

An anomaly,
a weirdness;

A rarity,
an oddness
#vss365

2D Convolution Old Blender project that I would like to implement purely in geometry-nodes.. wish I could use custom Python code :( #b3d #aestheticml #convolution


Presenting a novel approach to enhance the #spatiotemporalanalysis of #forest cosystems: “d'Alembert #Convolution for Enhanced Spatio-Temporal Analysis of Forest Ecosystems“ by R. Maskeliūnas, R. Damaševičius. ACSIS Vol. 39 p. 141–148; tinyurl.com/4fsw9583

annals_csis's tweet image. Presenting a novel approach to enhance the #spatiotemporalanalysis of #forest cosystems: “d'Alembert #Convolution for Enhanced Spatio-Temporal Analysis of Forest Ecosystems“ by R. Maskeliūnas, R. Damaševičius. ACSIS Vol. 39 p. 141–148; tinyurl.com/4fsw9583

#つぶやきGLSL #RT #convolution float i,e,g,v;for(o++;i++<95.;o-=.027/exp(e*1e4)){vec3 p=vec3((FC.xy*2.-r)/r.x*g*.25,0);p.z=(p.z+=-1.3-(sin(t*1.5)*.15));e=p.z*g;for(v=4.;v<49.;e+=abs(dot(fract(p.xz*v),(r/r/v))))p.zy*=rotate2D(v+=v);g+=e=.5+reflect(e*.08,p.y*p.x*p.z*p.z)*1.5;}


Dynamic Schwartz-Fourier Neural Operator for Enhanced Expressive Power Wenhan Gao, Jian Luo, Ruichen Xu, Yi Liu. Action editor: Fuxin Li. openreview.net/forum?id=B0E2y… #convolutions #transforms #convolution


I've been meaning to try #convolution/#IR #reverb for a long time. It means making a loud bang, so I have to remember during the day so as not to freak out the neighbours. I just made a few bangs. These little Chinese firecrackers are evil! True stereo, not for today.

danja's tweet image. I&apos;ve been meaning to try #convolution/#IR #reverb for a long time. It means making a loud bang, so I have to remember during the day so as not to freak out the neighbours. I just made a few bangs.
These little Chinese firecrackers are evil! 
True stereo, not for today.
danja's tweet image. I&apos;ve been meaning to try #convolution/#IR #reverb for a long time. It means making a loud bang, so I have to remember during the day so as not to freak out the neighbours. I just made a few bangs.
These little Chinese firecrackers are evil! 
True stereo, not for today.
danja's tweet image. I&apos;ve been meaning to try #convolution/#IR #reverb for a long time. It means making a loud bang, so I have to remember during the day so as not to freak out the neighbours. I just made a few bangs.
These little Chinese firecrackers are evil! 
True stereo, not for today.

🖼️🖼️ A Lightweight #CNN Based on Axial Depthwise #Convolution and Hybrid Attention for Remote Sensing #Image #Dehazing ✍️ Yufeng He et al. 🔗 brnw.ch/21wRcSu

RemoteSens_MDPI's tweet image. 🖼️🖼️ A Lightweight #CNN Based on Axial Depthwise #Convolution and Hybrid Attention for Remote Sensing #Image #Dehazing

✍️ Yufeng He et al.
🔗 brnw.ch/21wRcSu

Presenting a novel approach to enhance the #spatiotemporalanalysis of #forest cosystems: “d'Alembert #Convolution for Enhanced Spatio-Temporal Analysis of Forest Ecosystems“ by R. Maskeliūnas, R. Damaševičius. ACSIS Vol. 39 p. 141–148; tinyurl.com/4fsw9583

annals_csis's tweet image. Presenting a novel approach to enhance the #spatiotemporalanalysis of #forest cosystems: “d&apos;Alembert #Convolution for Enhanced Spatio-Temporal Analysis of Forest Ecosystems“ by R. Maskeliūnas, R. Damaševičius. ACSIS Vol. 39 p. 141–148; tinyurl.com/4fsw9583

Dynamic Schwartz-Fourier Neural Operator for Enhanced Expressive Power Wenhan Gao, Jian Luo, Ruichen Xu, Yi Liu. Action editor: Fuxin Li. openreview.net/forum?id=B0E2y… #convolutions #transforms #convolution


A #convolution to the assembly An insanity to the genius A blot to the brightness A balance to the quiver A hinderance to the continuance A treasure to the lacking A difference to the apathy An eeriness, a uniqueness An anomaly, a weirdness; A rarity, an oddness #vss365

Folabz_'s tweet image. A #convolution
to the assembly

An insanity
to the genius

A blot
to the brightness

A balance
to the quiver

A hinderance
to the continuance

A treasure
to the lacking

A difference
to the apathy

An eeriness,
a uniqueness

An anomaly,
a weirdness;

A rarity,
an oddness
#vss365

Synchron Stage Reverb Lite by @viennasymphlib Vienna Symphonic Library — FREE convolution reverb 🏟️🎶 Iconic Vienna Stage A ambience with cinematic warmth & clarity macOS & Windows (VST, VST3, AU, AAX) 🔗 vsl.co.at/ssr-lite-1 #reverb #convolution #cinematic #freevst

LEGAL_VST's tweet image. Synchron Stage Reverb Lite by @viennasymphlib  Vienna Symphonic Library — FREE convolution reverb 🏟️🎶

Iconic Vienna Stage A ambience with cinematic warmth &amp;amp; clarity
macOS &amp;amp; Windows (VST, VST3, AU, AAX)  
🔗 vsl.co.at/ssr-lite-1

#reverb #convolution #cinematic #freevst

Presenting a novel approach to enhance the #spatiotemporalanalysis of #forest cosystems: “d'Alembert #Convolution for Enhanced Spatio-Temporal Analysis of Forest Ecosystems“ by R. Maskeliūnas, R. Damaševičius. ACSIS Vol. 39 p. 141–148; tinyurl.com/4fsw9583

annals_csis's tweet image. Presenting a novel approach to enhance the #spatiotemporalanalysis of #forest cosystems: “d&apos;Alembert #Convolution for Enhanced Spatio-Temporal Analysis of Forest Ecosystems“ by R. Maskeliūnas, R. Damaševičius. ACSIS Vol. 39 p. 141–148; tinyurl.com/4fsw9583

🖼️🖼️ A Lightweight #CNN Based on Axial Depthwise #Convolution and Hybrid Attention for Remote Sensing #Image #Dehazing ✍️ Yufeng He et al. 🔗 brnw.ch/21wRcSu

RemoteSens_MDPI's tweet image. 🖼️🖼️ A Lightweight #CNN Based on Axial Depthwise #Convolution and Hybrid Attention for Remote Sensing #Image #Dehazing

✍️ Yufeng He et al.
🔗 brnw.ch/21wRcSu

🖼️🖼️ HVConv: Horizontal and Vertical #Convolution for Remote Sensing #Object #Detection ✍️ Jinhui Chen et al. 🔗 brnw.ch/21wQNZX

RemoteSens_MDPI's tweet image. 🖼️🖼️ HVConv: Horizontal and Vertical #Convolution for Remote Sensing #Object #Detection

✍️ Jinhui Chen et al.
🔗 brnw.ch/21wQNZX

Quick code view! 👀 A clean 1D Convolution in Python :) #Python #Convolution #CNNs

igorlrazevedo's tweet image. Quick code view! 👀 
A clean 1D Convolution in Python :)

#Python #Convolution #CNNs

🖼️🖼️ A Renovated Framework of a #Convolution #NeuralNetwork with Transformer for Detecting #Surface Changes from #HighResolution Remote-Sensing #Images ✍️ Shunyu Yao et al. 🔗 brnw.ch/21wTMAa

RemoteSens_MDPI's tweet image. 🖼️🖼️ A Renovated Framework of a #Convolution #NeuralNetwork with Transformer for Detecting #Surface Changes from #HighResolution Remote-Sensing #Images

✍️ Shunyu Yao et al.
🔗 brnw.ch/21wTMAa

👋👋 RG-GCN: A Random Graph Based on Graph #Convolution #Network for #PointCloud Semantic #Segmentation ✍️ Ziyin Zeng et al. 🔗 brnw.ch/21wPwQP

RemoteSens_MDPI's tweet image. 👋👋 RG-GCN: A Random Graph Based on Graph #Convolution #Network for #PointCloud Semantic #Segmentation

✍️ Ziyin Zeng et al.
🔗 brnw.ch/21wPwQP

👉 #LiteSTNet: A Hybrid Model of Lite #SwinTransformer and #Convolution for #BuildingExtraction from Remote Sensing Image ✍️ Yuan, W. et al. 📎 brnw.ch/21wNkh2

RemoteSens_MDPI's tweet image. 👉 #LiteSTNet: A Hybrid Model of Lite #SwinTransformer and #Convolution for #BuildingExtraction from Remote Sensing Image

✍️ Yuan, W. et al.
📎 brnw.ch/21wNkh2

👉👉 RoadFormer: #Road Extraction Using a Swin #Transformer Combined with a Spatial and Channel Separable #Convolution ✍️ Xiangzeng Liu et al. 🔗 mdpi.com/2072-4292/15/4…

RemoteSens_MDPI's tweet image. 👉👉 RoadFormer: #Road Extraction Using a Swin #Transformer Combined with a Spatial and Channel Separable #Convolution

✍️ Xiangzeng Liu et al.
🔗 mdpi.com/2072-4292/15/4…

After adjusting the booleanization threshold, I achieved a peak accuracy of 92.67% on the #FashionMNIST dataset using a tiny #TsetlinMachine model with 20 clauses per class and a simple #convolution.

ArtemHnilov's tweet image. After adjusting the booleanization threshold, I achieved a peak accuracy of 92.67% on the #FashionMNIST dataset using a tiny #TsetlinMachine model with 20 clauses per class and a simple #convolution.

🖼️🖼️ Attention Mechanism and Depthwise Separable #Convolution Aided #3DCNN for #Hyperspectral Remote Sensing Image #Classification ✍️ Wenmei Li et al. 🔗 brnw.ch/21wPpqR

RemoteSens_MDPI's tweet image. 🖼️🖼️ Attention Mechanism and Depthwise Separable #Convolution Aided #3DCNN for #Hyperspectral Remote Sensing Image #Classification

✍️ Wenmei Li et al.
🔗 brnw.ch/21wPpqR

🖼️🖼️ A Multi-Scale Mask #Convolution-Based Blind-Spot #Network for #Hyperspectral Anomaly #Detection ✍️ Zhiwei Yang et al. 🔗 brnw.ch/21wTnk3

RemoteSens_MDPI's tweet image. 🖼️🖼️ A Multi-Scale Mask #Convolution-Based Blind-Spot #Network for #Hyperspectral Anomaly #Detection

✍️ Zhiwei Yang et al.
🔗 brnw.ch/21wTnk3

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