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Huge! @TianhongLi6 & Kaiming He (inventor of ResNet) just Introduced JiT (Just image Transformers)! JiTs are simple large-patch Transformers that operate on raw pixels, no tokenizer, pre-training, or extra losses needed. By predicting clean data on the natural-data manifold,

Day 195 : DataScience Journey VGG16 Run Concludes Strong : 99.12% Train Accuracy & 98.78% Validation Moving Forward with ResNet Arch : ResNet paper 2015 (He et al.) : Deep Residual Learning for Image Recognition;) Training concluded with exceptional results ; 99.12% training

< Choosing a Vision Backbone > your model’s backbone is its perspective pick ResNet, and it sees in edges pick a ViT, and it sees in patches the backbone decides how your model thinks here are some of the most practical backbones and when you should choose them, from the

最近在 B 站又跟着李沐读了不少 AI 论文，再次推荐他的《AI 论文精读》系列， https://t.co/kHPEKq15gG 论文的结构大多八股：摘要、引言、方法、实验、结论，一板一眼。但要把这样的内容讲得清晰易懂、让人愿意听下去，其实特别难。这考验的不是文笔，而是对问题本质的洞察力。 ResNet

ResNet (2015) deeper networks were supposed to be better, but they weren't. add more layers and training error goes UP. ResNet made deep neural networks work by introducing skip connections, enabling networks with >50 layers. last day! ML papers day 7: a thread →

in an alternate timeline the resnet paper never gained traction fractal nets are introduced in the paper "fractalnet: ultra-deep neural networks" in their place to much celebration the transformer now use fractal pathway instead of residuals no one understand whats going on

Free Course to learn Deep Learning Concepts. Link is in the comment. > This course is a conceptual and architectural journey through deep learning vision models, tracing the evolution from LeNet and AlexNet to ResNet, EfficientNet, and Vision Transformers. > The course explains

ResNet paper discussion this Sunday on our discord if anyone would like to join

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AWS demands $32.77/hour for A100 GPU access, pricing out 90% of indie devs from AI innovation. VFTChain's Optimus app flips this: Train ResNet, BERT, or Stable Diffusion 70-95% cheaper on your hardware, data secure and local.

data from it is actually running thru ResNet and LSTM now, low inference latency (<200 us) for high repetition rate real time control. Hirschman2025: [A hybrid neural architecture: Online attosecond x-ray characterization]( https://t.co/WoThLALDrD)

Ever feel like AI development is pricing you out? Those massive GPU bills from big clouds add up fast, and shady token launches just burn retail investors. Enter VFTChain's AI Client: 147 models baked in (from ResNet to Stable Diffusion), delivering 92% savings on compute...

RESNET® Board of Directors Selects Shelby Gatlin as New Executive Director https://t.co/69DUL8yQSM

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Day 29, 30 | Winter arc update ❄️ - faced a major issue while working with sentinel-2 images (solved by my teammate) - planned extraction and inference pipeline - started learning about ResNet

Neural networks aren't abstract math. They're architecture decisions at scale. Every layer is a filtering stage. Every connection is a weighted pathway. Every activation function is a decision boundary. The difference between ResNet and Transformer isn't complexity. It's which

Cloud AI costs are exploding—AWS charges thousands for simple model training, sidelining indie devs and startups from the $500B market. VFTChain Optimus flips the script: Train ResNet, BERT, and more right on your desktop, slashing costs 70-95% with total data privacy.

Enhancing intensification forecast of tropical cyclones in the North Indian Ocean Basin using fused Vision transformer and Convolutional block attention with ResNet model The proposed vision HASTVi model shows the Mean absolute error (MAE) of 2.90 kts, 3.14 kts, and 5.38 kts,