#deeplearningneuralnetwork search results

Sensors MDPI

Jan 30, 2024

#highlycitedpaper Deep Learning Automated Segmentation for Muscle and Adipose Tissue from Abdominal Computed Tomography in Polytrauma Patients mdpi.com/1424-8220/21/6… #sarcopenia #deeplearningneuralnetwork #automatedsegmentation #computedtomography

Sensors MDPI

@Sensors_MDPI

Nov 24, 2021

Novel Ensemble Approach of #DeepLearningNeuralNetwork (#DLNN) Model and #ParticleSwarmOptimization (#PSO) Algorithm for Prediction of #GullyErosionSusceptibility @UniDuyTan @bauhaus_uni 👉mdpi.com/1424-8220/20/1… #erosion #hazardmap #naturalhazard #spatialmodel #RemoteSensing

Sensors MDPI

@Sensors_MDPI

Jan 30, 2024

No results for "#deeplearningneuralnetwork"

Python Programming

@PythonPr

Oct 4

Convolutional Neural Networks | Deep Learning

🔥 Holy shit... Apple just did something nobody saw coming They just dropped Pico-Banana-400K a 400,000-image dataset for text-guided image editing that might redefine multimodal training itself. Here’s the wild part: Unlike most “open” datasets that rely on synthetic…

alex_prompter's tweet image. 🔥 Holy shit... Apple just did something nobody saw coming

They just dropped Pico-Banana-400K a 400,000-image dataset for text-guided image editing that might redefine multimodal training itself.

Here’s the wild part:

Unlike most “open” datasets that rely on synthetic…

God of Prompt

@godofprompt

Oct 20

🚨 DeepSeek just did something wild. They built an OCR system that compresses long text into vision tokens literally turning paragraphs into pixels. Their model, DeepSeek-OCR, achieves 97% decoding precision at 10× compression and still manages 60% accuracy even at 20×. That…

godofprompt's tweet image. 🚨 DeepSeek just did something wild.

They built an OCR system that compresses long text into vision tokens literally turning paragraphs into pixels.

Their model, DeepSeek-OCR, achieves 97% decoding precision at 10× compression and still manages 60% accuracy even at 20×. That…

Guy Yariv

@guy_yariv

Oct 24

We present DyPE, a framework for ultra high resolution image generation. DyPE adjusts positional embeddings to evolve dynamically with the spectral progression of diffusion. This lets pre-trained DiTs create images with 16M+ pixels without retraining or extra inference cost. 🧵👇

guy_yariv's tweet image. We present DyPE, a framework for ultra high resolution image generation.
DyPE adjusts positional embeddings to evolve dynamically with the spectral progression of diffusion.
This lets pre-trained DiTs create images with 16M+ pixels without retraining or extra inference cost.
🧵👇

Kirk Borne

@KirkDBorne

Oct 14

Practical #MachineLearning for #ComputerVision — End-to-End ML for Images: amzn.to/4ajfVSf ———— #BigData #DataScience #AI #DeepLearning #NeuralNetworks

KirkDBorne's tweet image. Practical #MachineLearning for #ComputerVision — End-to-End ML for Images: amzn.to/4ajfVSf
————
#BigData #DataScience #AI #DeepLearning #NeuralNetworks

Saining Xie

@sainingxie

Oct 14

three years ago, DiT replaced the legacy unet with a transformer-based denoising backbone. we knew the bulky VAEs would be the next to go -- we just waited until we could do it right. today, we introduce Representation Autoencoders (RAE). >> Retire VAEs. Use RAEs. 👇(1/n)

sainingxie's tweet image. three years ago, DiT replaced the legacy unet with a transformer-based denoising backbone. we knew the bulky VAEs would be the next to go -- we just waited until we could do it right.

today, we introduce Representation Autoencoders (RAE).

&gt;&gt; Retire VAEs. Use RAEs. 👇(1/n)

kache

@yacineMTB

Oct 6, 2024

hey bro i trained a new resolution upscaling neural network check it out

AssistantX_AI

@AssistantX_chat

Oct 23

This new Deepseek release might have some AI labs rethinking if they should switch from using text and tokens to using… pixels.

AssistantX_chat's tweet image. This new Deepseek release might have some AI labs rethinking if they should switch from using text and tokens to using… pixels.

leonxt

@_tusharrathore

19 h

This architecture represents how a Convolutional Neural Network (CNN) transforms raw images into intelligent predictions. Through layers of Convolution, ReLU, Pooling, and Fully Connected Networks, it learns to see, understand, and classify — just like the human brain.

_tusharrathore's tweet image. This architecture represents how a Convolutional Neural Network (CNN) transforms raw images into intelligent predictions.
Through layers of Convolution, ReLU, Pooling, and Fully Connected Networks, it learns to see, understand, and classify — just like the human brain.

Alejo

@ecommartinez

14 h

Toma ChatGPT y crea esta foto tuya: retrato de doble exposición de una persona Prompt: Double exposure portrait of a person, profile view, looking left, with snow-covered pine trees and falling snow integrated into their silhouette and hair. The person has a thoughtful…

vLLM

@vllm_project

Oct 20

🚀 DeepSeek-OCR — the new frontier of OCR from @deepseek_ai , exploring optical context compression for LLMs, is running blazingly fast on vLLM ⚡ (~2500 tokens/s on A100-40G) — powered by vllm==0.8.5 for day-0 model support. 🧠 Compresses visual contexts up to 20× while keeping…

vllm_project's tweet image. 🚀 DeepSeek-OCR — the new frontier of OCR from @deepseek_ai , exploring optical context compression for LLMs, is running blazingly fast on vLLM ⚡ (~2500 tokens/s on A100-40G) — powered by vllm==0.8.5 for day-0 model support.

🧠 Compresses visual contexts up to 20× while keeping…

ゆっきー

@sakenomiya_n

2 h

これはフィルタ使ってる見る人が見ればわかると思うけど、一見わかりにくい #SNPIT

Pratima Adhikari

@pratimaadhikary

Oct 23

I don’t know if you guys have used Xiaomi’s filter options ( in their Leica optimised phones ) but they’re really good 📸 Xiaomi 15T Pro

pratimaadhikary's tweet image. I don’t know if you guys have used Xiaomi’s filter options ( in their Leica optimised phones ) but they’re really good
📸 Xiaomi 15T Pro

Tom Dörr

@tom_doerr

Jun 28

Image super-resolution and restoration tool using deep learning models

AIandFred(AI机器人和我)

@mingweihehehe

2 h

一幅图解释deepseek OCR模型的原理：如何将｛文本信息tokens｝高准确率的压缩成｛视觉tokens｝

Ray Fernando

@RayFernando1337

Oct 20

This is the JPEG moment for AI. Optical compression doesn't just make context cheaper. It makes AI memory architectures viable. Training data bottlenecks? Solved. - 200k pages/day on ONE GPU - 33M pages/day on 20 nodes - Every multimodal model is data-constrained. Not anymore.…

RayFernando1337's tweet image. This is the JPEG moment for AI.

Optical compression doesn't just make context cheaper. It makes AI memory architectures viable.

Training data bottlenecks? Solved.
- 200k pages/day on ONE GPU
- 33M pages/day on 20 nodes
- Every multimodal model is data-constrained. Not anymore.…

Mahesh Lambe

@Mahesh_Lambe

19 m

Just dropped: DeepSeek-OCR flips the script on language models by turning text into pictures. The vision-based encoder compresses long documents into 10x fewer tokens with 97% accuracy—storing pages as images so LLMs can remember more. This changes everything. Please Bookmark,…

Mahesh_Lambe's tweet image. Just dropped: DeepSeek-OCR flips the script on language models by turning text into pictures. The vision-based encoder compresses long documents into 10x fewer tokens with 97% accuracy—storing pages as images so LLMs can remember more. This changes everything. Please Bookmark,…

Deep-ML

@real_deep_ml

Oct 21

New Deep-ML Collection based on the AlexNet Paper, you could only learn so much from reading, the best way to learn is by solving!

real_deep_ml's tweet image. New Deep-ML Collection based on the AlexNet Paper, you could only learn so much from reading, the best way to learn is by solving!

Federico Baldassarre

@BaldassarreFe

Aug 14

Say hello to DINOv3 🦖🦖🦖 A major release that raises the bar of self-supervised vision foundation models. With stunning high-resolution dense features, it’s a game-changer for vision tasks! We scaled model size and training data, but here's what makes it special 👇