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CNN (Convolutional Neural Network) Visualization

Interesting As Fuck

2,056,351 subscribers

390,097 Aufrufe • vor 1 Jahr •via X (Twitter)

Bildung Wissenschaft & Technologie Kunst

Anya Rossi• Live Now

Private livecam show

11 Kommentare

Profilbild von Motion

Motionvor 1 Jahr

this is cool #Elon #Zelena #Trump #Entertainment #Tommavi #Helevier #GrandeFratello #Uzaksehir #Shailenzo #Yulioli #Zeudiners #CR7 #BBB25 #NBA #UFC #CTESPN #bbvipal4 #sstvi

Profilbild von Dr Shad Katuu 🌐

Dr Shad Katuu 🌐vor 3 Jahren

#blockchain innovations and the contribution of the intergovernmental organizations #OpenAccess

Profilbild von Jason Balazs

Jason Balazsvor 1 Jahr

That's beautiful

Profilbild von Harry Berries

Harry Berriesvor 1 Jahr

idk wtf I'm looking at, but it's cool.

Profilbild von KOVNAH

KOVNAHvor 1 Jahr

ok I thought it was the fake news network one

Profilbild von gökhan

gökhanvor 1 Jahr

What’s your favorite CNN use case?

Profilbild von MsInterpreted

MsInterpretedvor 1 Jahr

This is so interesting

Profilbild von AJ

AJvor 1 Jahr

The visualizations are right there

Profilbild von 𝐊𝐞𝐞𝐫𝐭𝐡𝐢 𝐑𝐚𝐣

𝐊𝐞𝐞𝐫𝐭𝐡𝐢 𝐑𝐚𝐣vor 1 Jahr

😲

Profilbild von Zero Supremo

Zero Supremovor 1 Jahr

sooo a really slow and unnecessary animation to patter recognition.....ok

Profilbild von ✨Ray say Rano✨

✨Ray say Rano✨vor 1 Jahr

Amazing technology 👏👏

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Fukushima's video (1986) shows a CNN that recognises handwritten digits [3], three years before LeCun's video (1989). CNN timeline taken from [5]: ★ 1969: Kunihiko Fukushima published rectified linear units or ReLUs [1] which are now extensively used in CNNs. ★ 1979: Fukushima published the basic CNN architecture with convolution layers and downsampling layers [2]. He called it neocognitron. It was trained by unsupervised learning rules. Compute was 100 times more expensive than in 1989, and a billion times more expensive than today. ★ 1986: Fukushima's video on recognising hand-written digits [3]. ★ 1988: Wei Zhang et al had the first "modern" 2-dimensional CNN trained by backpropagation, and also applied it to character recognition [4]. Compute was about 10 million times more expensive than today. ★ 1989-: later work by others [5]. REFERENCES (more in [5]) [1] K. Fukushima (1969). Visual feature extraction by a multilayered network of analog threshold elements. IEEE Transactions on Systems Science and Cybernetics. 5 (4): 322-333. This work introduced rectified linear units or ReLUs, now widely used in CNNs and other neural nets. [2] K. Fukushima (1979). Neural network model for a mechanism of pattern recognition unaffected by shift in position—Neocognitron. Trans. IECE, vol. J62-A, no. 10, pp. 658-665, 1979. The first deep convolutional neural network architecture, with alternating convolutional layers and downsampling layers. In Japanese. English version: 1980. [3] Movie produced by K. Fukushima, S. Miyake and T. Ito (NHK Science and Technical Research Laboratories), in 1986. YouTube: [4] W. Zhang, J. Tanida, K. Itoh, Y. Ichioka. Shift-invariant pattern recognition neural network and its optical architecture. Proc. Annual Conference of the Japan Society of Applied Physics, 1988. First "modern" backpropagation-trained 2-dimensional CNN, applied to character recognition. [5] J. Schmidhuber (AI Blog, 2025). Who invented convolutional neural networks?

Fukushima's video (1986) shows a CNN that recognises handwritten digits [3], three years before LeCun's video (1989). CNN timeline taken from [5]: ★ 1969: Kunihiko Fukushima published rectified linear units or ReLUs [1] which are now extensively used in CNNs. ★ 1979: Fukushima published the basic CNN architecture with convolution layers and downsampling layers [2]. He called it neocognitron. It was trained by unsupervised learning rules. Compute was 100 times more expensive than in 1989, and a billion times more expensive than today. ★ 1986: Fukushima's video on recognising hand-written digits [3]. ★ 1988: Wei Zhang et al had the first "modern" 2-dimensional CNN trained by backpropagation, and also applied it to character recognition [4]. Compute was about 10 million times more expensive than today. ★ 1989-: later work by others [5]. REFERENCES (more in [5]) [1] K. Fukushima (1969). Visual feature extraction by a multilayered network of analog threshold elements. IEEE Transactions on Systems Science and Cybernetics. 5 (4): 322-333. This work introduced rectified linear units or ReLUs, now widely used in CNNs and other neural nets. [2] K. Fukushima (1979). Neural network model for a mechanism of pattern recognition unaffected by shift in position—Neocognitron. Trans. IECE, vol. J62-A, no. 10, pp. 658-665, 1979. The first deep convolutional neural network architecture, with alternating convolutional layers and downsampling layers. In Japanese. English version: 1980. [3] Movie produced by K. Fukushima, S. Miyake and T. Ito (NHK Science and Technical Research Laboratories), in 1986. YouTube: [4] W. Zhang, J. Tanida, K. Itoh, Y. Ichioka. Shift-invariant pattern recognition neural network and its optical architecture. Proc. Annual Conference of the Japan Society of Applied Physics, 1988. First "modern" backpropagation-trained 2-dimensional CNN, applied to character recognition. [5] J. Schmidhuber (AI Blog, 2025). Who invented convolutional neural networks?

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