#آموزش
Recognizing Speech Commands Using Recurrent Neural Networks with Attention
https://towardsdatascience.com/recognizing-speech-commands-using-recurrent-neural-networks-with-attention-c2b2ba17c837
سورس کد:
A Keras implementation of neural attention model for speech command recognition
https://github.com/douglas125/SpeechCmdRecognition
مرتبط با:
سورس و مقاله wav2letter++ یک روش end2end
https://news.1rj.ru/str/cvision/850
جلسه مربوط به Attention در RNNها:
https://www.aparat.com/v/SPZzH
جلسه مربوط به پردازش صوت در RNNها:
https://www.aparat.com/v/cEKal
#attention #rnn #lstm #keras #Speech
Recognizing Speech Commands Using Recurrent Neural Networks with Attention
https://towardsdatascience.com/recognizing-speech-commands-using-recurrent-neural-networks-with-attention-c2b2ba17c837
سورس کد:
A Keras implementation of neural attention model for speech command recognition
https://github.com/douglas125/SpeechCmdRecognition
مرتبط با:
سورس و مقاله wav2letter++ یک روش end2end
https://news.1rj.ru/str/cvision/850
جلسه مربوط به Attention در RNNها:
https://www.aparat.com/v/SPZzH
جلسه مربوط به پردازش صوت در RNNها:
https://www.aparat.com/v/cEKal
#attention #rnn #lstm #keras #Speech
Medium
Recognizing Speech Commands Using Recurrent Neural Networks with Attention
Speech recognition has become an integral part of human-computer interfaces (HCI). They are present in personal assistants like Google…
#Fun
تاثیر بلاگ medium در مباحث یادگیری عمیق...
تاثیر بلاگ medium در مباحث یادگیری عمیق...
#سورس_کد #مقاله
دو پروژه مرتبط، یکی برای تشخیص موقعیت سه بعدی چهره، در شرایط سخت، از جمله
extreme viewing conditions, including near profile views, occlusions, and low resolution.
و پروژه دیگر، برای مدل سازی سه بعدی چهره، برای data augmentation
که میتوانید از ماتریس موقعیت پروژه اول، برای افزونگی داده در پروژه دوم استفاده کنید.
Face-Pose-Net
Estimate 3D face pose (6DoF) or 11 parameters of 3x4 projection matrix by a Convolutional Neural Network
https://github.com/fengju514/Face-Pose-Net
face_specific_augm
Face Renderer to perform Domain (Face) Specific Data Augmentation
https://github.com/iacopomasi/face_specific_augm
مقالات مرتبط
FacePoseNet: Making a Case for Landmark-Free Face Alignment
https://arxiv.org/abs/1708.07517
Do We Really Need to Collect Millions of Faces for Effective Face Recognition?
http://www.openu.ac.il/home/hassner/projects/augmented_faces/Masietal2016really.pdf
#face #pose #data_augmentation
دو پروژه مرتبط، یکی برای تشخیص موقعیت سه بعدی چهره، در شرایط سخت، از جمله
extreme viewing conditions, including near profile views, occlusions, and low resolution.
و پروژه دیگر، برای مدل سازی سه بعدی چهره، برای data augmentation
که میتوانید از ماتریس موقعیت پروژه اول، برای افزونگی داده در پروژه دوم استفاده کنید.
Face-Pose-Net
Estimate 3D face pose (6DoF) or 11 parameters of 3x4 projection matrix by a Convolutional Neural Network
https://github.com/fengju514/Face-Pose-Net
face_specific_augm
Face Renderer to perform Domain (Face) Specific Data Augmentation
https://github.com/iacopomasi/face_specific_augm
مقالات مرتبط
FacePoseNet: Making a Case for Landmark-Free Face Alignment
https://arxiv.org/abs/1708.07517
Do We Really Need to Collect Millions of Faces for Effective Face Recognition?
http://www.openu.ac.il/home/hassner/projects/augmented_faces/Masietal2016really.pdf
#face #pose #data_augmentation
GitHub
GitHub - fengju514/Face-Pose-Net: Estimate 3D face pose (6DoF) or 11 parameters of 3x4 projection matrix by a Convolutional Neural…
Estimate 3D face pose (6DoF) or 11 parameters of 3x4 projection matrix by a Convolutional Neural Network - GitHub - fengju514/Face-Pose-Net: Estimate 3D face pose (6DoF) or 11 parameters of 3x4 pro...
#مقاله
شمارش افراد در جمعیت
Mask-aware networks for crowd counting
https://arxiv.org/pdf/1901.00039.pdf
شمارش افراد در جمعیت
Mask-aware networks for crowd counting
https://arxiv.org/pdf/1901.00039.pdf
مقالات و پیاده سازی های شمارش افراد در جمعیت:
Awesome-Crowd-Counting
https://github.com/gjy3035/Awesome-Crowd-Counting
#Code
#Tools
#Datasets
#Papers
#Leaderboard
پست مرتبط:
https://news.1rj.ru/str/cvision/887
#Crowd_Counting
Awesome-Crowd-Counting
https://github.com/gjy3035/Awesome-Crowd-Counting
#Code
#Tools
#Datasets
#Papers
#Leaderboard
پست مرتبط:
https://news.1rj.ru/str/cvision/887
#Crowd_Counting
GitHub
GitHub - gjy3035/Awesome-Crowd-Counting: Awesome Crowd Counting
Awesome Crowd Counting. Contribute to gjy3035/Awesome-Crowd-Counting development by creating an account on GitHub.
کامنت گذاری خودکار کدها با شبکه های LSTM !
Automatically generating code comments directly from source code using an LSTM. Works with multiple languages. Would be useful in any IDE.
https://www.twosixlabs.com/automatically-generating-comments-for-arbitrary-source-code/
Automatically generating code comments directly from source code using an LSTM. Works with multiple languages. Would be useful in any IDE.
https://www.twosixlabs.com/automatically-generating-comments-for-arbitrary-source-code/
Two Six Labs | Advanced Analytics, Cyber Capabilities, Tactical Mobility Solutions for National Security
Automatically Generating Comments for Arbitrary Source Code - Two Six Labs | Advanced Analytics, Cyber Capabilities, Tactical Mobility…
#خبر
پیش بینی افراد سرشناس از هوش مصنوعی در سال 2019
AI predictions for 2019 from Yann LeCun, Hilary Mason, Andrew Ng, and Rumman Chowdhury
https://venturebeat.com/2019/01/02/ai-predictions-for-2019-from-yann-lecun-hilary-mason-andrew-ng-and-rumman-chowdhury/
پیش بینی افراد سرشناس از هوش مصنوعی در سال 2019
AI predictions for 2019 from Yann LeCun, Hilary Mason, Andrew Ng, and Rumman Chowdhury
https://venturebeat.com/2019/01/02/ai-predictions-for-2019-from-yann-lecun-hilary-mason-andrew-ng-and-rumman-chowdhury/
Can we compress the knowledge of a large dataset into a small number of synthetically generated images? Researchers at FAIR, MIT, and Berkeley investigate in their paper: http://bit.ly/2GvWnAy
🙏Thanks to: @vahidreza01
🙏Thanks to: @vahidreza01
#InstaGAN Excels in Instance-Aware Image-To-Image Translation
https://medium.com/syncedreview/instagan-excels-in-instance-aware-image-to-image-translation-64fb7d0344ae
https://medium.com/syncedreview/instagan-excels-in-instance-aware-image-to-image-translation-64fb7d0344ae
#مقاله
یک کار جدید Image to image Translation
https://news.1rj.ru/str/cvision/892
مقاله:
https://arxiv.org/pdf/1812.10889.pdf
کد:
https://github.com/sangwoomo/instagan
The paper #InstaGAN: Instance-Aware Image-to-Image Translation has been accepted by the respected International Conference on Learning Representations (#ICLR) 2019, which will take place this May in New Orleans, USA.
This new research is based on #CycleGAN, a GAN variant which can learn to translate images without paired training data to overcome the limitations of one-by-one pairing of #pix2pix in image translation. CycleGAN can automatically translate two given unordered image sets X and Y, but it cannot encode instance information in an image. CycleGAN results however are not ideal when translating images involving specific features of the target. The InstaGAN system overcomes this problem and combines instance information from multiple task targets.
کارها و مطالب مشابه و مرتبط:
https://news.1rj.ru/str/cvision/214
https://news.1rj.ru/str/cvision/870
https-://t.me/cvision/863
#Image_to_Image_Translation #GAN
یک کار جدید Image to image Translation
https://news.1rj.ru/str/cvision/892
مقاله:
https://arxiv.org/pdf/1812.10889.pdf
کد:
https://github.com/sangwoomo/instagan
The paper #InstaGAN: Instance-Aware Image-to-Image Translation has been accepted by the respected International Conference on Learning Representations (#ICLR) 2019, which will take place this May in New Orleans, USA.
This new research is based on #CycleGAN, a GAN variant which can learn to translate images without paired training data to overcome the limitations of one-by-one pairing of #pix2pix in image translation. CycleGAN can automatically translate two given unordered image sets X and Y, but it cannot encode instance information in an image. CycleGAN results however are not ideal when translating images involving specific features of the target. The InstaGAN system overcomes this problem and combines instance information from multiple task targets.
کارها و مطالب مشابه و مرتبط:
https://news.1rj.ru/str/cvision/214
https://news.1rj.ru/str/cvision/870
https-://t.me/cvision/863
#Image_to_Image_Translation #GAN
Telegram
Tensorflow
#InstaGAN Excels in Instance-Aware Image-To-Image Translation
https://medium.com/syncedreview/instagan-excels-in-instance-aware-image-to-image-translation-64fb7d0344ae
https://medium.com/syncedreview/instagan-excels-in-instance-aware-image-to-image-translation-64fb7d0344ae
#سورس_کد
#InstaGAN
این مقاله نقص های cycleGan را رفع کرده.
#PyTorch implementation of "InstaGAN: Instance-aware Image Translation" (ICLR 2019)
code:
https://github.com/sangwoomo/instagan
paper:
https://arxiv.org/pdf/1812.10889.pdf
blog post:
https://news.1rj.ru/str/cvision/892
بیشتر:
https://news.1rj.ru/str/cvision/893
#Image_to_Image_Translation #GAN
#InstaGAN
این مقاله نقص های cycleGan را رفع کرده.
#PyTorch implementation of "InstaGAN: Instance-aware Image Translation" (ICLR 2019)
code:
https://github.com/sangwoomo/instagan
paper:
https://arxiv.org/pdf/1812.10889.pdf
blog post:
https://news.1rj.ru/str/cvision/892
بیشتر:
https://news.1rj.ru/str/cvision/893
#Image_to_Image_Translation #GAN
سری توئیت های اندرونگ
1/The rise of Software Engineering required inventing processes like version control, code review, agile, to help teams work effectively. The rise of AI & Machine Learning Engineering is now requiring new processes, like how we split train/dev/test, model zoos, etc.
2/I'm also seeing many AI teams use new processes that haven't been formalized or named yet, ranging from how we write product requirement docs to how we version data and ML pipelines. This is an exciting time for developing these ideas!
3/Have you seen an idea for organizing ML projects that you'd like to share with others? If so please reply to this tweet!
https://twitter.com/AndrewYNg/status/1080886439380869122
1/The rise of Software Engineering required inventing processes like version control, code review, agile, to help teams work effectively. The rise of AI & Machine Learning Engineering is now requiring new processes, like how we split train/dev/test, model zoos, etc.
2/I'm also seeing many AI teams use new processes that haven't been formalized or named yet, ranging from how we write product requirement docs to how we version data and ML pipelines. This is an exciting time for developing these ideas!
3/Have you seen an idea for organizing ML projects that you'd like to share with others? If so please reply to this tweet!
https://twitter.com/AndrewYNg/status/1080886439380869122
Twitter
Andrew Ng
1/The rise of Software Engineering required inventing processes like version control, code review, agile, to help teams work effectively. The rise of AI & Machine Learning Engineering is now requiring new processes, like how we split train/dev/test, model…