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🌟 SEE-2-SOUND - a method for generating complex spatial sound based on images and videos
— pip install see2sound
🖥 GitHub
🟡 Hugging Face
🟡 Arxiv
@Machine_learn
— pip install see2sound
🖥 GitHub
🟡 Hugging Face
🟡 Arxiv
@Machine_learn
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Seq2Seq: Sequence-to-Sequence Generator
🖥 Github: https://github.com/fiy2w/mri_seq2seq
📕 Paper: https://arxiv.org/abs/2407.02911v1
🔥Dataset: https://paperswithcode.com/task/contrastive-learning
@Machine_learn
🖥 Github: https://github.com/fiy2w/mri_seq2seq
📕 Paper: https://arxiv.org/abs/2407.02911v1
🔥Dataset: https://paperswithcode.com/task/contrastive-learning
@Machine_learn
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سلام دوستانی که مقاله دارن می تونن به این ژورنال بفرستن و من و به عنوان داور معرفی کنن
@Machine_learn
@Machine_learn
👍8❤3🔥1
Minutes to Seconds: Speeded-up DDPM-based Image Inpainting with Coarse-to-Fine Sampling
🖥 Github: https://github.com/linghuyuhangyuan/m2s
📕 Paper: https://arxiv.org/abs/2407.05875v1
🔥Dataset: https://paperswithcode.com/task/denoising
@Machine_learn
🔥Dataset: https://paperswithcode.com/task/denoising
@Machine_learn
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👁🗨 LongVA: Long Context Transfer from Language to Vision
▪Github: https://github.com/EvolvingLMMs-Lab/LongVA
▪Paper: https://arxiv.org/abs/2406.16852
▪Project: https://lmms-lab.github.io/posts/longva/
▪Demo: https://longva-demo.lmms-lab.com/
@Machine_learn
▪Github: https://github.com/EvolvingLMMs-Lab/LongVA
▪Paper: https://arxiv.org/abs/2406.16852
▪Project: https://lmms-lab.github.io/posts/longva/
▪Demo: https://longva-demo.lmms-lab.com/
@Machine_learn
❤1🔥1
Unified Embedding Alignment for Open-Vocabulary Video Instance Segmentation (ECCV 2024)
🖥 Github: https://github.com/fanghaook/ovformer
📕 Paper: https://arxiv.org/abs/2407.07427v1
@Machine_learn
@Machine_learn
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Multimodal contrastive learning for spatial gene expression prediction using histology images
🖥 Github: https://github.com/modelscope/data-juicer
📕 Paper: https://arxiv.org/abs/2407.08583v1
🚀 Dataset: https://paperswithcode.com/dataset/coco
@Machine_learn
🚀 Dataset: https://paperswithcode.com/dataset/coco
@Machine_learn
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🌟 An Empirical Study of Mamba-based Pedestrian Attribute Recognition
🖥 Github: https://github.com/event-ahu/openpar
📕 Paper: https://arxiv.org/pdf/2407.10374v1.pdf
🚀 Dataset: https://paperswithcode.com/dataset/peta
@Machine_learn
🚀 Dataset: https://paperswithcode.com/dataset/peta
@Machine_learn
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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
🚀 Dataset: https://paperswithcode.com/dataset/is3-interactive-synthetic-sound-source
@Machine_learn
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🌟 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
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
👍2
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
🖥 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
🔥3
🚀 Dataset: https://paperswithcode.com/dataset/behave
@Machine_learn
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⚡️ EMO-Disentanger
🖥 Github: https://github.com/yuer867/emo-disentanger
📕 Paper: https://arxiv.org/abs/2407.20955v1
🚀 Dataset: https://paperswithcode.com/dataset/emopia
@Machine_learn
🚀 Dataset: https://paperswithcode.com/dataset/emopia
@Machine_learn
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👍3
How to Think Like a Computer Scientist: Interactive Edition
https://runestone.academy/ns/books/published/thinkcspy/index.html
@Machine_learn
https://runestone.academy/ns/books/published/thinkcspy/index.html
@Machine_learn
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No learning rates needed: Introducing SALSA - Stable Armijo Line Search Adaptation
🖥 Github: https://github.com/themody/no-learning-rates-needed-introducing-salsa-stable-armijo-line-search-adaptation
📕 Paper: https://arxiv.org/abs/2407.20650v1
🚀 Dataset: https://paperswithcode.com/dataset/cifar-10
✅ @Machine_learn
🖥 Github: https://github.com/themody/no-learning-rates-needed-introducing-salsa-stable-armijo-line-search-adaptation
📕 Paper: https://arxiv.org/abs/2407.20650v1
🚀 Dataset: https://paperswithcode.com/dataset/cifar-10
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https://research.google/blog/scaling-hierarchical-agglomerative-clustering-to-trillion-edge-graphs/
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Pixart-Sigma, the first high-quality, transformer-based image generation training framework!
🖥 Github: https://github.com/PixArt-alpha/PixArt-sigma
🔥Demo: https://huggingface.co/spaces/PixArt-alpha/PixArt-Sigma
✅ @Machine_learn
🔥Demo: https://huggingface.co/spaces/PixArt-alpha/PixArt-Sigma
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GitHub
GitHub - PixArt-alpha/PixArt-sigma: PixArt-Σ: Weak-to-Strong Training of Diffusion Transformer for 4K Text-to-Image Generation
PixArt-Σ: Weak-to-Strong Training of Diffusion Transformer for 4K Text-to-Image Generation - PixArt-alpha/PixArt-sigma
Recall-Oriented-CL-Framework
🖥 Github: https://github.com/bigdata-inha/recall-oriented-cl-framework
📕 Paper: https://arxiv.org/pdf/2403.03082v1.pdf
🔥Dataset: https://paperswithcode.com/dataset/cifar-10
✨ Tasks: https://paperswithcode.com/task/continual-learning
✅ @Machine_learn
🔥Dataset: https://paperswithcode.com/dataset/cifar-10
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GitHub
GitHub - bigdata-inha/recall-oriented-cl-framework
Contribute to bigdata-inha/recall-oriented-cl-framework development by creating an account on GitHub.
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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
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
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