Researchers propose a transfer learning strategy for fault identification of deep fault-karst #carbonate. #openaccess at https://www.sciencedirect.com/science/article/pii/S2352854025000221. #Seismicfault #Transferlearning #ArtificialIntelligence
Administered by:
#transferlearning
0 posts0 participants0 posts today
https://www.europesays.com/uk/134411/ Smart neural network and cognitive computing process for multi task nuclei detection segmentation and classification in breast cancer histopathology images #BreastCancer #Cancer #ClassificationModel #Computing #DeepLearning #HistopathologyImages #HumanitiesAndSocialSciences #multidisciplinary #NucleiSegmentation #Science #Technology #TransferLearning #UK #UnitedKingdom
How to classify Malaria Cells using Convolutional neural network
You can find link for the code in the blog : https://eranfeit.net/how-to-classify-malaria-cells-using-convolutional-neural-network/
Check out our tutorial here : https://youtu.be/WlPuW3GGpQo&list=UULFTiWJJhaH6BviSWKLJUM9sg
Enjoy
Eran
https://www.europesays.com/1759609/ Intelligent skin disease prediction system using transfer learning and explainable artificial intelligence #AI #AndLayerWiseRelevancePropagation(LRP) #ArtificialIntelligence #ArtificialIntelligenceAI #Chickenpox #ComputationalScience #COMPUTERSCIENCE #DeepLearning(DL) #ExplainableArtificialIntelligence(XAI) #HumanitiesAndSocialSciences #MachineLearning(ML) #Measles #monkeypox #multidisciplinary #science #SkinCancer #Software #TransferLearning(TL) #VGG16
https://phys.org/news/2024-12-ai-world-temperatures-3c-faster.html
(wishing this were hallucination..)
Key findings
Using #AI-based #transferlearning, the researchers analyzed data from 10 different #climatemodels to predict temperature increases and found:
‣ 34 regions are likely to exceed 1.5°C of warming by 2040.
‣ 31 of these 34 regions are expected to reach 2°C of warming by 2040.
‣ 26 of these 34 regions are projected to surpass 3°C of warming by 2060.
Barnes*, Diffenbaugh and Seneviratne
DOI10.1088/1748-9326/ad91ca
Phys.org · AI predicts that most of the world will see temperatures rise to 3°C much faster than previously expected
This is such a cool dataset: 22 different robots demonstrating 527 skills through a collaboration between 21 research institutions.
And the GIFs of all these different robots applying basic motor skills are adorable.
robotics-transformer-x.github.ioOpen X-Embodiment: Robotic Learning Datasets and RT-X ModelsProject page for Open X-Embodiment: Robotic Learning Datasets and RT-X Models.
In our latest video tutorial, we will create a dog breed recognition model using the NasLarge pre-trained model 
and a massive dataset featuring over 10,000 images of 120 unique dog breeds 
.
Check out our tutorial here : https://youtu.be/vH1UVKwIhLo&list=UULFTiWJJhaH6BviSWKLJUM9sg
You can find link for the code in the blog : https://eranfeit.net/120-dog-breeds-more-than-10000-images-deep-learning-tutorial-for-dogs-classification/
Enjoy
Eran
Don’t Push the Button! Exploring Data Leakage Risks in Machine Learning and Transfer Learning.
I came across a diagram illustrating transfer learning in the ML textbook I'm currently in the middle of, and it looked an awful lot like diagrams for natural transformations. I bet I'm not the first person to have noticed that, or the tenth. Any interesting papers I ought to read?
4M: Massively Multimodal Masked Modeling
#4MModell, #ComputerVision, #Multimodalität, #MaschinellesLernen, #NeuronaleNetze, #AIRevolution, #Bildbearbeitung, #TransferLearning, #GenerativeModelle, #ZukunftDerTechnologie
https://kinews24.de/4m-massively-multimodal-masked-modeling/
KI NEWS24 · 4M: Massively Multimodal Masked Modeling - KINEWS24.de4M: Massively Multimodal Masked Modeling
Discover the power of transfer learning in machine learning! Learn about techniques, benefits, and overcoming challenges. 
Check it out: https://ak-codes.com/transfer-learning/ #MachineLearning #TransferLearning
AK codes · Harnessing the Power of Transfer Learning - AK codesDiscover the impact of transfer learning in machine learning, covering techniques, benefits, challenges, and ways to overcome limitations.
Dive into this fascinating example of transfer learning and hyperparameter tuning for image classification tasks! 
#MachineLearning #TransferLearning #HyperparameterTuning https://ak-codes.com/transfer-learning-example/
AK codes · Transfer Learning And Hyperparameter Tuning Example - AK codesLearn more about how to implement transfer learning and hyperparameter tuning in this example for a classification task using images.
Deep #MachineLearning for #meteor monitoring - advances with #TransferLearning and gradient-weighted class activation mapping: https://arxiv.org/abs/2310.16826 -> long thread https://nitter.net/Eloy_PeAs/status/1717528486657597883
Proud to announce our new paper, "Relevant Entity Selection: Knowledge Graph Bootstrapping via Zero-Shot Analogical Pruning" with Lucas Jarnac and Miguel Couceiro, accepted in #cikm2023
Contrarily to the hype, #AI is contributing to increase #carbonfootprint. I wrote a short summary, and proposed few ideas (sparse #neuralnetworks, simpler #LLM models, #neuromorphic hardware, #federatedlearning, #transferlearning)
https://alecrimi.substack.com/p/ai-carbon-footprint
#ml #sustainability
5 emerging trends in deep learning and artificial intelligence - Explore five emerging trends in deep learning and artificial inte... - https://cointelegraph.com/news/5-emerging-trends-in-deep-learning-and-artificial-intelligence #reinforcementlearning #federatedlearning #transferlearning #explainableai #deeplearning #transparency #dataprivacy
Learning fast and slow 
Highly excited that our (long-term) work on more flexible #ReinforcementLearning and #TransferLearning is finally public.
Two separate processes enable fast, coarse adaptation and slow, but better final performance.
#Newpaper: Our work for #nlproc on segmenting conversational data is now out on @NeuripsConf (#ENLSP)
We find that reusing pre-trained feature hierarchy in a #transferlearning paradigm proves to be ineffective for topic segmentation tasks on chat data.
Topic Segmentation in the Wild:Towards Segmentation of Semi-structured & Unstructured Chats w. Harjeet S, Sharanya K, Dhuri S, Samyadeep B, Soundar S, #Umass #Microsoft 
Paper: https://arxiv.org/abs/2211.14954
Please DM to meetup @ #NeurIPS2022 :)
arXiv.orgTopic Segmentation in the Wild: Towards Segmentation of Semi-structured & Unstructured ChatsBreaking down a document or a conversation into multiple contiguous segments
based on its semantic structure is an important and challenging problem in NLP,
which can assist many downstream tasks. However, current works on topic
segmentation often focus on segmentation of structured texts. In this paper, we
comprehensively analyze the generalization capabilities of state-of-the-art
topic segmentation models on unstructured texts. We find that: (a) Current
strategies of pre-training on a large corpus of structured text such as
Wiki-727K do not help in transferability to unstructured texts. (b) Training
from scratch with only a relatively small-sized dataset of the target
unstructured domain improves the segmentation results by a significant margin.
Want to share a milestone on a #ml #project I’ve been working on for a while on the side. I’m working on a #computervision application for #chess to detect the game state from a photo.
I used #transferlearning to fine tune a #convolutionalneuralnetwork with a new head for #regression to predict the four corners of the board.
I found synthetic datasets online (~6k images) and labeled ~1k real photos. I trained the model with a mix of random augmentations and projections with small errors.
Detect possible interactions between drugs using out-of-the-box Relation Extraction #SparkNLP model.
Live-demo: http://hubs.li/Q01sLGy_0
#datascience #textmining #healthcareai #deeplearning #machinelearning #artificialintelligence #transferlearning #healthcaredatamining #nlp #nlproc
demo.johnsnowlabs.comStreamlit