Have you heard of "R-Transformer?", a Recurrent Neural Network Enhanced Transformer
Recurrent Neural Networks have long been the dominating choice for sequence modeling. However, it severely suffers from two issues: impotent in capturing very long-term dependencies and unable to parallelize the sequential computation procedure.
Therefore, many non-recurrent sequence models that are built on convolution and attention operations have been proposed recently.
Here the authors propose the R-Transformer which enjoys the advantages of both RNNs and the multi-head attention mechanism while avoids their respective drawbacks.
The proposed model can effectively capture both local structures and global long-term dependencies in sequences without any use of position embeddings. They evaluated R-Transformer through extensive experiments with data from a wide range of domains and the empirical results show that R-Transformer outperforms the state-of-the-art methods by a large margin in most of the tasks.
Github code: https://lnkd.in/dpFckix
#research #algorithms #machinelearning #deeplearning #rnn
β΄οΈ @AI_Python_EN
Recurrent Neural Networks have long been the dominating choice for sequence modeling. However, it severely suffers from two issues: impotent in capturing very long-term dependencies and unable to parallelize the sequential computation procedure.
Therefore, many non-recurrent sequence models that are built on convolution and attention operations have been proposed recently.
Here the authors propose the R-Transformer which enjoys the advantages of both RNNs and the multi-head attention mechanism while avoids their respective drawbacks.
The proposed model can effectively capture both local structures and global long-term dependencies in sequences without any use of position embeddings. They evaluated R-Transformer through extensive experiments with data from a wide range of domains and the empirical results show that R-Transformer outperforms the state-of-the-art methods by a large margin in most of the tasks.
Github code: https://lnkd.in/dpFckix
#research #algorithms #machinelearning #deeplearning #rnn
β΄οΈ @AI_Python_EN
Awesome victory for #DeepLearning ππ»
GE Healthcare wins FDA clearance for #algorithms to spot type of collapsed lung!
Hereβs how the AI algorithm works
ββββββββββββββββ
1. A patient image scanned on a device is automatically searched for pneumothorax.
2. If pneumothorax is suspected, an alert with the original chest X-ray, is sent to the radiologist to review.
3. That technologist would also receive an on-device notification to highlight prioritized cases.
4. Algorithms would then analyze and flag protocol and field of view errors and auto rotate images on device.
Article is here:
https://lnkd.in/daNYHfP
#machinelearning
GE Healthcare wins FDA clearance for #algorithms to spot type of collapsed lung!
Hereβs how the AI algorithm works
ββββββββββββββββ
1. A patient image scanned on a device is automatically searched for pneumothorax.
2. If pneumothorax is suspected, an alert with the original chest X-ray, is sent to the radiologist to review.
3. That technologist would also receive an on-device notification to highlight prioritized cases.
4. Algorithms would then analyze and flag protocol and field of view errors and auto rotate images on device.
Article is here:
https://lnkd.in/daNYHfP
#machinelearning
Medgadget
GE Healthcare's Artificial Intelligence FDA Cleared to Help Spot Collapsed Lung |
Admitted patients often have to wait a number of hours for a radiologist to review their chest X-ray, even though it may be marked as urgent or STAT.
Understanding the Backpropagation Algorithm.
#BigData #DataScience #AI #MachineLearning #IoT #IIoT #PyTorch #Python #TensorFlow #CloudComputing #Algorithms
http://bit.ly/2ASKwqx
βοΈ @AI_Python_EN
#BigData #DataScience #AI #MachineLearning #IoT #IIoT #PyTorch #Python #TensorFlow #CloudComputing #Algorithms
http://bit.ly/2ASKwqx
βοΈ @AI_Python_EN
Mish is now even supported on YOLO v3 backend. Couldn't have been more elated with how rewarding this project has been. Link to repository -
https://github.com/digantamisra98/Mish
#neuralnetworks #mathematics #algorithms #deeplearning #machinelearning
βοΈ @AI_Python_EN
https://github.com/digantamisra98/Mish
#neuralnetworks #mathematics #algorithms #deeplearning #machinelearning
βοΈ @AI_Python_EN
A good introduction to #MachineLearning and its 4 approaches:
https://towardsdatascience.com/machine-learning-an-introduction-23b84d51e6d0?gi=10a5fcd4decd
#BigData #DataScience #AI #Algorithms #ReinforcementLearning
βοΈ @AI_Python_EN
https://towardsdatascience.com/machine-learning-an-introduction-23b84d51e6d0?gi=10a5fcd4decd
#BigData #DataScience #AI #Algorithms #ReinforcementLearning
βοΈ @AI_Python_EN