🌟 MG-LLaVA - multimodal LLM with advanced capabilities for working with visual information

Just recently, the guys from Shanghai University rolled out MG-LLaVA - MLLM, which expands the capabilities of processing visual information through the use of additional components: special components that are responsible for working with low and high resolution.

MG-LLaVA integrates an additional high-resolution visual encoder to capture fine details, which are then combined with underlying visual features using the Conv-Gate network.

Trained exclusively on publicly available multimodal data, MG-LLaVA achieves excellent results.

🟡 MG-LLaVA page
🖥 GitHub

@Machine_learn

Aligning Sight and Sound: Advanced Sound Source Localization Through Audio-Visual Alignment

🖥 Github: https://github.com/kaistmm/SSLalignment

📕 Paper: https://arxiv.org/abs/2407.13676v1

🚀 Dataset: https://paperswithcode.com/dataset/is3-interactive-synthetic-sound-source

@Machine_learn

با عرض سلام دو پکیچ یادگیری ماشین و یادگیری عمیق را برای دوستانی که می خواهند تا فرداشب با تخفیف ۵۰٪ مجدد قرار دادیم این تخفیف اخرین سری از تخفیف های این دو پکیچ می باشد
1: introduction to machine learning
2: Regression (linear and non-linear)
3: Tensorflow introduction
4: Tensorflow computaion graph
5: Tensorflow optimizer and loss function
6: Tensorflow linear and non linear regression
7: logistic regression
8: Tensorflow regression
___________
9: introduction to traditional machine learning
*10: knn and desicion tree
*11: desicion tree and Naive bayes
*12: desicion tree, knn, Naive bayes implementation
*13: k-means
*14: Guassion Mixture Model(GMM)
*15: implementation K-means and GMM
_
16: introduction to Artificial Neural Network
17: Multi-level Neural Network
18: Introduction to Convolution Neural Network
19: Tensorflow Multi-level Neural Network
20:Tensorflow CNN
21:CNN image clasaification
22: Cnn text clasaification
23: Recurrent Neural Network(RNN)

جهت تهیه می تونین به ایدی بنده مراجعه کنین

@Raminmousa

Recurrent Neural Networks Learn to Store and Generate Sequences
using Non-Linear Representations

#RNN

https://arxiv.org/pdf/2408.10920


@Machine_learn