Тренируем нейронную сеть написанную на TensorFlow в облаке, с помощью Google Cloud ML и Cloud Shell
Конвертер моделей darknet на tensorflow.
Load trained weights, retrain/fine-tune them using tensorflow, export constant graph def to C++
https://github.com/thtrieu/darkflow
Load trained weights, retrain/fine-tune them using tensorflow, export constant graph def to C++
https://github.com/thtrieu/darkflow
Recurrent Shop
Framework for building complex recurrent neural networks with Keras
Recurrent shop providing a set of RNNCells, which can be added sequentially to a special layer called RecurrentContainer along with other layers such as Dropout and Activation, very similar to adding layers to a Sequential model in Keras. The RecurrentContainer then behaves like a standard Keras Recurrent instance. In case of RNN stacks, the computation is done depth-first, which results in significant speed ups.
https://github.com/datalogai/recurrentshop
#keras
Framework for building complex recurrent neural networks with Keras
Recurrent shop providing a set of RNNCells, which can be added sequentially to a special layer called RecurrentContainer along with other layers such as Dropout and Activation, very similar to adding layers to a Sequential model in Keras. The RecurrentContainer then behaves like a standard Keras Recurrent instance. In case of RNN stacks, the computation is done depth-first, which results in significant speed ups.
https://github.com/datalogai/recurrentshop
#keras
Music auto-tagging models
and trained weights in keras/theano
How was it trained?
Using 29.1s music files in Million Song Dataset
split setting: A repo for split setting for an identical setting.
See https://arxiv.org/pdf/1609.04243v3.pdf
https://github.com/keunwoochoi/music-auto_tagging-keras
https://github.com/keunwoochoi/music-auto_tagging-keras/blob/master/slide-ismir-2016.pdf
#keras
and trained weights in keras/theano
How was it trained?
Using 29.1s music files in Million Song Dataset
split setting: A repo for split setting for an identical setting.
See https://arxiv.org/pdf/1609.04243v3.pdf
https://github.com/keunwoochoi/music-auto_tagging-keras
https://github.com/keunwoochoi/music-auto_tagging-keras/blob/master/slide-ismir-2016.pdf
#keras
SalGAN: Visual Saliency Prediction with Generative Adversarial Networks
saliency-salgan-2017
https://imatge-upc.github.io/saliency-salgan-2017/
https://github.com/imatge-upc/saliency-salgan-2017
#Lasagne #theano #salience
saliency-salgan-2017
https://imatge-upc.github.io/saliency-salgan-2017/
https://github.com/imatge-upc/saliency-salgan-2017
#Lasagne #theano #salience
YOLO9000 (детектирование 9000 категорий!)
We introduce YOLO9000, a state-of-the-art, real-time object detection system that can detect over 9000 object categories. First we propose various improvements to the YOLO detection method, both novel and drawn from prior work.
https://arxiv.org/pdf/1612.08242v1.pdf
https://www.reddit.com/r/MachineLearning/comments/5kr31v/r_yolo_9000/
http://pjreddie.com/yolo9000/
#yolo
We introduce YOLO9000, a state-of-the-art, real-time object detection system that can detect over 9000 object categories. First we propose various improvements to the YOLO detection method, both novel and drawn from prior work.
https://arxiv.org/pdf/1612.08242v1.pdf
https://www.reddit.com/r/MachineLearning/comments/5kr31v/r_yolo_9000/
http://pjreddie.com/yolo9000/
#yolo
Запись лекций с конференции
AINL FRUCT: Artificial Intelligence and Natural Language Conference
(Русские лекторы на англ. яз.)
DL Часть1 - https://www.lektorium.tv/lecture/29462#
DL Часть2 - https://www.lektorium.tv/lecture/29464
Все лекции https://www.lektorium.tv/conference/29503
AINL FRUCT: Artificial Intelligence and Natural Language Conference
(Русские лекторы на англ. яз.)
DL Часть1 - https://www.lektorium.tv/lecture/29462#
DL Часть2 - https://www.lektorium.tv/lecture/29464
Все лекции https://www.lektorium.tv/conference/29503
Blockchains for Artificial Intelligence
from Decentralized Model Exchanges to Model Audit Trails
https://blog.bigchaindb.com/blockchains-for-artificial-intelligence-ec63b0284984#.homr8nm11
from Decentralized Model Exchanges to Model Audit Trails
https://blog.bigchaindb.com/blockchains-for-artificial-intelligence-ec63b0284984#.homr8nm11