Large Brain Model for Learning Generic Representations with Tremendous EEG Data in BCI
🖥 Github: https://github.com/935963004/labram
📕 Paper: https://arxiv.org/abs/2405.18765v1
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Forwarded from Papers
سلام دوستاني كه مقاله براي ارسال به ژورنال دارن مي تونن بنده رو به عنوان داور در سه ژورنال زير معرفي كنند
1-Knowledge-Based system(https://www.sciencedirect.com/journal/knowledge-based-systems)
2-Machine learning with application(https://www.sciencedirect.com/journal/machine-learning-with-applications)
3-Ai(https://www.sciencedirect.com/journal/artificial-intelligence)
Name:Ramin Mousa
Email: [email protected]
همچنين دوستاني كه مقاله براي ارسال دارن مي تونن قبل ارسال جهت بررسي به بنده ارسال كنن تا يك پيش داوري انجام بدم.
@Raminmousa
@Paper4money
@Machine_learn
1-Knowledge-Based system(https://www.sciencedirect.com/journal/knowledge-based-systems)
2-Machine learning with application(https://www.sciencedirect.com/journal/machine-learning-with-applications)
3-Ai(https://www.sciencedirect.com/journal/artificial-intelligence)
Name:Ramin Mousa
Email: [email protected]
همچنين دوستاني كه مقاله براي ارسال دارن مي تونن قبل ارسال جهت بررسي به بنده ارسال كنن تا يك پيش داوري انجام بدم.
@Raminmousa
@Paper4money
@Machine_learn
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TensorIR: An Abstraction for Automatic Tensorized Program Optimization
Paper: https://arxiv.org/pdf/2207.04296v2.pdf
Codes: https://github.com/mlc-ai/web-llm - https://github.com/apache/tvm
✅ @Machine_learn
Paper: https://arxiv.org/pdf/2207.04296v2.pdf
Codes: https://github.com/mlc-ai/web-llm - https://github.com/apache/tvm
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# setting up a venv:
conda create -n depth-pro -y python=3.9
conda activate depth-pro
pip install -e .
# Download pretrained checkpoints:
source get_pretrained_models.sh
# Run the inference from CLI on a single image:
depth-pro-run -i ./data/example.jpg
# Running from python
from PIL import Image
import depth_pro
model, transform = depth_pro.create_model_and_transforms()
model.eval()
image, _, f_px = depth_pro.load_rgb(image_path)
image = transform(image)
prediction = model.infer(image, f_px=f_px)
depth = prediction["depth"] # Depth in [m].
focallength_px = prediction["focallength_px"] # Focal length in pixels.@Machine_learn
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Deep Learning and Computational Physics - Lecture Notes, University of South California
📓 book
@Machine_learn
📓 book
@Machine_learn
❤5
Forwarded from Github LLMs
Crawl 4 AI
Crawl4AI: Open-source LLM Friendly Web Crawler & Scrapper
Creator: UncleCode
Stars ⭐️: 8.6k
Forked By: 627
https://github.com/unclecode/crawl4ai
✅ https://t.iss.one/deep_learning_proj
Crawl4AI: Open-source LLM Friendly Web Crawler & Scrapper
Creator: UncleCode
Stars ⭐️: 8.6k
Forked By: 627
https://github.com/unclecode/crawl4ai
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GitHub
GitHub - unclecode/crawl4ai: 🚀🤖 Crawl4AI: Open-source LLM Friendly Web Crawler & Scraper. Don't be shy, join here: https://dis…
🚀🤖 Crawl4AI: Open-source LLM Friendly Web Crawler & Scraper. Don't be shy, join here: https://discord.gg/jP8KfhDhyN - unclecode/crawl4ai
👍3
Generalizable and Animatable Gaussian Head Avatar
🖥 Github: https://github.com/xg-chu/gagavatar
📕 Paper: https://arxiv.org/abs/2410.07971v1
@Machine_learn
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👍1
با عرض سلام خيلي از دوستان در رابطه با طراحي صفر تا صد پروژه هاي ديپ از بنده سوال پرسيدن داخل پك زير ٣٦ پروژه رو با جزئيات شرح دادم:
1-Deep Learning Basic
-01_Introduction
--01_How_TensorFlow_Works
2-Classification apparel
-Classification apparel double capsule
-Classification apparel double cnn
3-ALZHEIMERS USING CNN(ResNet)
4-Fake News (Covid-19 dataset)
-Multi-channel
-3DCNN model
-Base line+ Char CNN
-Fake News Covid CapsuleNet
5-3DCNN Fake News
6-recommender systems
-GRU+LSTM MovieLens
7-Multi-Domain Sentiment Analysis
-Dranziera CapsuleNet
-Dranziera CNN Multi-channel
-Dranziera LSTM
8-Persian Multi-Domain SA
-Bi-GRU Capsule Net
-Multi-CNN
9-Recommendation system
-Factorization Recommender, Ranking Factorization Recommender, Item Similarity Recommender (turicreate)
-SVD, SVD++, NMF, Slope One, k-NN, Centered k-NN, k-NN Baseline, Co-Clustering(surprise)
10-NihX-Ray
-optimized CNN on FullDataset Nih-Xray
-MobileNet
-Transfer learning
-Capsule Network on FullDataset Nih-Xray
دوستاني كه نياز به اين پروژه ها دارن ميتونن با بنده در ارتباط باشن.
@Raminmousa
@Machine_learn
1-Deep Learning Basic
-01_Introduction
--01_How_TensorFlow_Works
2-Classification apparel
-Classification apparel double capsule
-Classification apparel double cnn
3-ALZHEIMERS USING CNN(ResNet)
4-Fake News (Covid-19 dataset)
-Multi-channel
-3DCNN model
-Base line+ Char CNN
-Fake News Covid CapsuleNet
5-3DCNN Fake News
6-recommender systems
-GRU+LSTM MovieLens
7-Multi-Domain Sentiment Analysis
-Dranziera CapsuleNet
-Dranziera CNN Multi-channel
-Dranziera LSTM
8-Persian Multi-Domain SA
-Bi-GRU Capsule Net
-Multi-CNN
9-Recommendation system
-Factorization Recommender, Ranking Factorization Recommender, Item Similarity Recommender (turicreate)
-SVD, SVD++, NMF, Slope One, k-NN, Centered k-NN, k-NN Baseline, Co-Clustering(surprise)
10-NihX-Ray
-optimized CNN on FullDataset Nih-Xray
-MobileNet
-Transfer learning
-Capsule Network on FullDataset Nih-Xray
دوستاني كه نياز به اين پروژه ها دارن ميتونن با بنده در ارتباط باشن.
@Raminmousa
@Machine_learn
👍7❤1
Efficiently Democratizing Medical LLMs for 50 Languages via a Mixture of Language Family Experts
💻 Github: https://github.com/freedomintelligence/apollomoe
🔖 Paper: https://arxiv.org/abs/2410.10626v1
🤗 Dataset: https://paperswithcode.com/dataset/mmlu
✅ @Machine_learn
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❤2👍1
Thesis2 2.pdf
5.5 MB
Thesis: Yolo object detection
این پروژه سال ۲۰۲۰ با یکی از دوستان انجام دادیم که هدف تشخیص وزن پل با استفاده از Yolo بود. جزئیات مدل یولو رو داخل این بررسی کردیم . برای دوستانی که می خوان بیشتر این مدل رو بررسی کنن می تونه مفید باشه.
@Machine_learn
این پروژه سال ۲۰۲۰ با یکی از دوستان انجام دادیم که هدف تشخیص وزن پل با استفاده از Yolo بود. جزئیات مدل یولو رو داخل این بررسی کردیم . برای دوستانی که می خوان بیشتر این مدل رو بررسی کنن می تونه مفید باشه.
@Machine_learn
🔥3