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CNN (Convolutional Neural Network) Visualization

Interesting As Fuck

2,056,351 subscribers

390,097 просмотров • 1 год назад •via X (Twitter)

Образование Наука и технологии Искусство

Anya Rossi• Live Now

Private livecam show

Комментарии: 11

Фото профиля Motion

Motion1 год назад

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

Фото профиля Dr Shad Katuu 🌐

Dr Shad Katuu 🌐3 лет назад

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

Фото профиля Jason Balazs

Jason Balazs1 год назад

That's beautiful

Фото профиля Harry Berries

Harry Berries1 год назад

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

Фото профиля KOVNAH

KOVNAH1 год назад

ok I thought it was the fake news network one

Фото профиля gökhan

gökhan1 год назад

What’s your favorite CNN use case?

Фото профиля MsInterpreted

MsInterpreted1 год назад

This is so interesting

Фото профиля AJ

AJ1 год назад

The visualizations are right there

Фото профиля 𝐊𝐞𝐞𝐫𝐭𝐡𝐢 𝐑𝐚𝐣

𝐊𝐞𝐞𝐫𝐭𝐡𝐢 𝐑𝐚𝐣1 год назад

😲

Фото профиля Zero Supremo

Zero Supremo1 год назад

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

Фото профиля ✨Ray say Rano✨

✨Ray say Rano✨1 год назад

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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