بعد از سه روز کاری سخت، عکس شیرین و تماشایی از مجموعه موبایل بیومتریک امبر
یه تشکر ویژه هم از همراه زندگی ام که صبورانه منتظره
دانشگاه سوم رم
رم ایتالیا
۱۱ می ۲۰۱۸
https://news.1rj.ru/str/Machinelearning_Kartal
یه تشکر ویژه هم از همراه زندگی ام که صبورانه منتظره
دانشگاه سوم رم
رم ایتالیا
۱۱ می ۲۰۱۸
https://news.1rj.ru/str/Machinelearning_Kartal
Ng_MLY04.pdf
437.2 KB
بخش23 تا 27 کتاب Machine Learning Yearning
از پروفسور
Andrew NG
منبع
ایمیل شده از سایت پروفسور
Andrew NG
با کانال
https://news.1rj.ru/str/Machinelearning_Kartal
همراه باشید.
از پروفسور
Andrew NG
منبع
ایمیل شده از سایت پروفسور
Andrew NG
با کانال
https://news.1rj.ru/str/Machinelearning_Kartal
همراه باشید.
چلنج مرتبط با کنفرانس CVPR همراه با جایزه هزار دلاری برای زمینه های مختلف کامپیوتر ویژن
we are excited to announce the 1st Robust Vision Challenge (ROB) in conjunction with CVPR 2018 in Salt Lake City! By now, all evaluation servers have been setup and baseline entries to our ROB leaderboards have been added. We are looking forward to your submissions!
http://www.robustvision.net
Submission deadline: June 1, 2018 (no extensions)
—---
The goal of our ROB challenge is to foster the development of vision systems that are robust and consequently perform well on a variety of datasets with different characteristics. To assess the robustness of algorithms, we evaluate algorithmic performance across various existing and novel datasets (indoors vs. outdoors, sunny vs. bad weather, various sensors, etc.). Our challenges include:
- Stereo matching
- Multi-view stereo
- Optical flow
- Single image depth prediction
- Semantic segmentation
- Semantic instance segmentation
For each challenge, the results of a single model must be submitted to all benchmarks. We encourage submissions of novel algorithms, techniques which are currently in review and methods that have already been published. The winners of each challenge will receive $1000 (1st place) and $500 (2nd place), present at our CVPR workshop and are invited to a joint dinner after the workshop. In addition, we plan a joint TPAMI journal submission with all winners.
We are now very much looking forward to your submissions!
The Robust Vision Challenge Team
Andreas Geiger, Matthias Nießner, Marc Pollefeys, Carsten Rother, Daniel Scharstein, Hassan Alhaija, Angela Dai, Katrin Honauer, Joel Janai, Torsten Sattler, Nick Schneider, Johannes Schönberger, Thomas Schöps, Jonas Uhrig, Jonas Wulff and Oliver Zendel
—----------------------------------------------------
— Unsubscribe
—----------------------------------------------------
* We send emails very rarely, but if you prefer to be removed permanently from our update list, simply send me (andreas.geiger@tue.mpg.de) an email with subject line "unsubscribe".
با کانال
https://news.1rj.ru/str/Machinelearning_Kartal/
همراه باشید.
we are excited to announce the 1st Robust Vision Challenge (ROB) in conjunction with CVPR 2018 in Salt Lake City! By now, all evaluation servers have been setup and baseline entries to our ROB leaderboards have been added. We are looking forward to your submissions!
http://www.robustvision.net
Submission deadline: June 1, 2018 (no extensions)
—---
The goal of our ROB challenge is to foster the development of vision systems that are robust and consequently perform well on a variety of datasets with different characteristics. To assess the robustness of algorithms, we evaluate algorithmic performance across various existing and novel datasets (indoors vs. outdoors, sunny vs. bad weather, various sensors, etc.). Our challenges include:
- Stereo matching
- Multi-view stereo
- Optical flow
- Single image depth prediction
- Semantic segmentation
- Semantic instance segmentation
For each challenge, the results of a single model must be submitted to all benchmarks. We encourage submissions of novel algorithms, techniques which are currently in review and methods that have already been published. The winners of each challenge will receive $1000 (1st place) and $500 (2nd place), present at our CVPR workshop and are invited to a joint dinner after the workshop. In addition, we plan a joint TPAMI journal submission with all winners.
We are now very much looking forward to your submissions!
The Robust Vision Challenge Team
Andreas Geiger, Matthias Nießner, Marc Pollefeys, Carsten Rother, Daniel Scharstein, Hassan Alhaija, Angela Dai, Katrin Honauer, Joel Janai, Torsten Sattler, Nick Schneider, Johannes Schönberger, Thomas Schöps, Jonas Uhrig, Jonas Wulff and Oliver Zendel
—----------------------------------------------------
— Unsubscribe
—----------------------------------------------------
* We send emails very rarely, but if you prefer to be removed permanently from our update list, simply send me (andreas.geiger@tue.mpg.de) an email with subject line "unsubscribe".
با کانال
https://news.1rj.ru/str/Machinelearning_Kartal/
همراه باشید.
Telegram
Machine learning application (Kartal)
1- Participate in cutting edge research in machine learning applications.
2- Apply your expertise in biometrics, Natural Language Processing, computer vision and real-time data mining solutions.
Admin: @Kartal_ai (https://news.1rj.ru/str/Kartal_ai )
2- Apply your expertise in biometrics, Natural Language Processing, computer vision and real-time data mining solutions.
Admin: @Kartal_ai (https://news.1rj.ru/str/Kartal_ai )
#ژورنال
یک سایت خوبه دیگه میتونید ژورنال مورد نظر حتی متناسب با موضوع مقالتون ارزیابی کنید
http://www.scimagojr.com
هست
مثلا در زمینه Computer sience و موضوع
Artificial Inteligence
این دوتا ژورنال رو ببینید
http://www.scimagojr.com/journalrank.php?area=1700&category=1702
http://www.scimagojr.com/journalsearch.php?q=24201&tip=sid&clean=0
حتی تو هیستوری می تونید مقایسه کنید که این ژورنال ها درباره اون فیلد چه عملکردی داشتن
کانال
https://news.1rj.ru/str/Machinelearning_Kartal/1353
با تشکر از علی اقای گل مدیر گروه اپلای کامپیوتر
یک سایت خوبه دیگه میتونید ژورنال مورد نظر حتی متناسب با موضوع مقالتون ارزیابی کنید
http://www.scimagojr.com
هست
مثلا در زمینه Computer sience و موضوع
Artificial Inteligence
این دوتا ژورنال رو ببینید
http://www.scimagojr.com/journalrank.php?area=1700&category=1702
http://www.scimagojr.com/journalsearch.php?q=24201&tip=sid&clean=0
حتی تو هیستوری می تونید مقایسه کنید که این ژورنال ها درباره اون فیلد چه عملکردی داشتن
کانال
https://news.1rj.ru/str/Machinelearning_Kartal/1353
با تشکر از علی اقای گل مدیر گروه اپلای کامپیوتر
Ng_MLY05.pdf
419.1 KB
بخش28 تا 30 کتاب Machine Learning Yearning
از پروفسور
Andrew NG
منبع
ایمیل شده از سایت پروفسور
Andrew NG
با کانال
https://news.1rj.ru/str/Machinelearning_Kartal/1354
همراه باشید
از پروفسور
Andrew NG
منبع
ایمیل شده از سایت پروفسور
Andrew NG
با کانال
https://news.1rj.ru/str/Machinelearning_Kartal/1354
همراه باشید
بورسیه تحصیلی در چین
USTB Excellent Freshmen Scholarships for International Students in China, 2018
The University of Science and Technology Beijing is inviting applications for USTB Excellent Freshmen Scholarships. These scholarships are open to international students who wish to pursue bachelor’s degree programme.
The University of Science and Technology Beijing, formerly known as Beijing Steel and Iron Institute before 1988, is a national key university in Beijing, China. USTB’s metallurgy and materials science programmes are highly regarded in China.
The candidate should have a very good command of English language. Therefore, the application should be written in English.
اطلاعات بیشتر و لینک ثبت نام
http://isc.ustb.edu.cn/en/template2.jsp?id=151
با تشکر از مهدی قیصری عزیز
با کانال
https://news.1rj.ru/str/Machinelearning_Kartal/1355
همراه باشید
USTB Excellent Freshmen Scholarships for International Students in China, 2018
The University of Science and Technology Beijing is inviting applications for USTB Excellent Freshmen Scholarships. These scholarships are open to international students who wish to pursue bachelor’s degree programme.
The University of Science and Technology Beijing, formerly known as Beijing Steel and Iron Institute before 1988, is a national key university in Beijing, China. USTB’s metallurgy and materials science programmes are highly regarded in China.
The candidate should have a very good command of English language. Therefore, the application should be written in English.
اطلاعات بیشتر و لینک ثبت نام
http://isc.ustb.edu.cn/en/template2.jsp?id=151
با تشکر از مهدی قیصری عزیز
با کانال
https://news.1rj.ru/str/Machinelearning_Kartal/1355
همراه باشید
Media is too big
VIEW IN TELEGRAM
یک راهنمای استفاده از تنسور فلو در اندروید که منبع و کدهای موجود در این راهنما در ادامه در همین کانال قرار داده می شود.
با کانال
https://news.1rj.ru/str/Machinelearning_Kartal/1356
همراه باشید
با کانال
https://news.1rj.ru/str/Machinelearning_Kartal/1356
همراه باشید
کد و راهنما های مورد نیاز تنسورفلو در اندروید ویدیو شماره ۱۳۵۶ به صورت زیر می باشد.
Let's create an Android app that uses a pre-trained Tensorflow image classifier for MNIST digits to recognize what the user draws on the screen. We'll use Android Studio and the gradle build system to make it happen.
Code for this video:
https://github.com/llSourcell/A_Guide_to_Running_Tensorflow_Models_on_Android
More learning resources:
https://www.tensorflow.org/mobile/
منبع اصلی ویدیو:
https://www.youtube.com/watch?v=kFWKdLOxykE
با کانال
https://news.1rj.ru/str/Machinelearning_Kartal/1357
همراه باشید
Let's create an Android app that uses a pre-trained Tensorflow image classifier for MNIST digits to recognize what the user draws on the screen. We'll use Android Studio and the gradle build system to make it happen.
Code for this video:
https://github.com/llSourcell/A_Guide_to_Running_Tensorflow_Models_on_Android
More learning resources:
https://www.tensorflow.org/mobile/
منبع اصلی ویدیو:
https://www.youtube.com/watch?v=kFWKdLOxykE
با کانال
https://news.1rj.ru/str/Machinelearning_Kartal/1357
همراه باشید
GitHub
GitHub - llSourcell/A_Guide_to_Running_Tensorflow_Models_on_Android: This is the code for"A Guide to Running Tensorflow Models…
This is the code for"A Guide to Running Tensorflow Models on Android" By SIraj Raval on Youtube - llSourcell/A_Guide_to_Running_Tensorflow_Models_on_Android
افتخار اردبیل
مهدی نورمحمدی خیارک (Laval university ) مقاله در ژورنال ایمپکت تقریبا سه.
تبریک داداش
@Machinelearning_Kartal
مهدی نورمحمدی خیارک (Laval university ) مقاله در ژورنال ایمپکت تقریبا سه.
تبریک داداش
@Machinelearning_Kartal
با سلام خدمت اعضای بزرگوار
خانم شهسواری از اعضای محترم کانال یک شماره سریال برا آزمون دستگاههای اجرایی دارند در واقع از سایت خریداری کرده اند و بنا به دلایلی از استفاده ان منصرف شده اند هر کدام از دوستان نیاز داشتند و تا بحال اقدام به خرید نکرده اند می توانند مال ایشون را بخرند و ایشالا دیگه پول ایشون هم پایمال نشه. باهم هستیم برای هم.
لطفا به ای دی ایشون پیام دهید.
@zazari569
با کانال ماشین لرنینگ
https://news.1rj.ru/str/Machinelearning_Kartal/1358
همراه هستید.
خانم شهسواری از اعضای محترم کانال یک شماره سریال برا آزمون دستگاههای اجرایی دارند در واقع از سایت خریداری کرده اند و بنا به دلایلی از استفاده ان منصرف شده اند هر کدام از دوستان نیاز داشتند و تا بحال اقدام به خرید نکرده اند می توانند مال ایشون را بخرند و ایشالا دیگه پول ایشون هم پایمال نشه. باهم هستیم برای هم.
لطفا به ای دی ایشون پیام دهید.
@zazari569
با کانال ماشین لرنینگ
https://news.1rj.ru/str/Machinelearning_Kartal/1358
همراه هستید.
مقاله برتر چهارمین کنفرانس داده بزرگ دانشگاه شهید مدنی اذربایجان با عنوان "تشخیص نویسنده از طریق رتبه بندی نویسنده بر مبنای احتمال تعلق متون"
فایل اصلی مقاله در ادامه
@Machinelearning_Kartal
فایل اصلی مقاله در ادامه
@Machinelearning_Kartal
BestPaper.pdf
612 KB
فایل اصلی مقاله برتر چهارمین کنفرانس داده بزرگ دانشگاه شهید مدنی اذربایجان
با تشکر از اشتراک گذاری دکتر مهدی هاشم زاده دبیر کمیته علمی کنفرانس
@Machinelearning_Kartal
با تشکر از اشتراک گذاری دکتر مهدی هاشم زاده دبیر کمیته علمی کنفرانس
@Machinelearning_Kartal
Machine learning application (Kartal)
با سلام خدمت اعضای بزرگوار خانم شهسواری از اعضای محترم کانال یک شماره سریال برا آزمون دستگاههای اجرایی دارند در واقع از سایت خریداری کرده اند و بنا به دلایلی از استفاده ان منصرف شده اند هر کدام از دوستان نیاز داشتند و تا بحال اقدام به خرید نکرده اند می توانند…
ممنون از اعضای محترم بابت خرید این.
من قبل از پذیرش دکترای خود جوابیه ای از یکی از اساتید ایتالیایی برای اپلای گرفته بودم که تمایل دارم برای دوستانی که در حوزه ماشین لرنینگ و کامپیوتر ویژن فعالیت می کنند به اشتراک بگذارم.
Dear Jalil,
it would be a pleasure to have you working with us in our lab.
However, to be admitted to a PhD course at the University of Pavia (and at an Italian university in general), you will need to participate in a public competition (composed of a qualification assessment and an interview).
The deadline for the 2017/18 application will be probably in July, and will be published at the page http://www.unipv.eu/site/en/home/research/phd-courses.html. Meanwhile, you can have a look at the 2016/17 call for applications: http://www.unipv.eu/site/en/home/research/phd-courses/documento27388.html, page 24 for the PhD in Electronics, Computer Science and Electrical Engineering).
Of course, in case you are interested, we will have to define a theme that you will propose in the interview.
امیدوارم مفید باشد.
با کانال ماشین لرنینگ
https://news.1rj.ru/str/Machinelearning_Kartal/1359
همراه هستید.
Dear Jalil,
it would be a pleasure to have you working with us in our lab.
However, to be admitted to a PhD course at the University of Pavia (and at an Italian university in general), you will need to participate in a public competition (composed of a qualification assessment and an interview).
The deadline for the 2017/18 application will be probably in July, and will be published at the page http://www.unipv.eu/site/en/home/research/phd-courses.html. Meanwhile, you can have a look at the 2016/17 call for applications: http://www.unipv.eu/site/en/home/research/phd-courses/documento27388.html, page 24 for the PhD in Electronics, Computer Science and Electrical Engineering).
Of course, in case you are interested, we will have to define a theme that you will propose in the interview.
امیدوارم مفید باشد.
با کانال ماشین لرنینگ
https://news.1rj.ru/str/Machinelearning_Kartal/1359
همراه هستید.
Ng_MLY06.pdf
391.5 KB
بخش32 تا 31 کتاب Machine Learning Yearning
از پروفسور
Andrew NG
منبع
ایمیل شده از سایت پروفسور
Andrew NG
با کانال
https://news.1rj.ru/str/Machinelearning_Kartal/1360
همراه باشید
از پروفسور
Andrew NG
منبع
ایمیل شده از سایت پروفسور
Andrew NG
با کانال
https://news.1rj.ru/str/Machinelearning_Kartal/1360
همراه باشید
چالش جدید دیگر از سایت https://www.kaggle.com
🌹انتخاب به عنوان کار تحقیقاتی جدید
🌿 انتخاب عنوان برای پایان نامه برای دوستان و دانشجویان ارشد عزیز.
💭برای بچه هایی که دنبال چالش و دنبال جایزه خوب
YouTube-8M Video Understanding Competition Launch: Create a Constrained-Size Model to Predict Video Labels
حامی اصلی این رقابت
Google AI
..🌹🌹🌹🌿🌿🌿🌹💭🌿
We've just launched the YouTube-8M Video Understanding Challenge! Here are the competition details. Click the button below if you're interested in competing, or digging deeper into the specifics.
Competition Denoscription:
This is the second Kaggle competition based on the YouTube 8M dataset, a large-scale video dataset that consists of millions of YouTube video features and associated labels from a diverse vocabulary of 3,700+ visual entities.
This year, the competition is focused on learning video representation under budget constraints. You’re challenge is to produce the best compact video classification model under 1GB.
YouTube
Host:
This competition is being hosted by Google AI (previously known as Google Research) as a part of the European Conference on Computer Vision (ECCV) 2018 selected workshop session.
Total prizes:
$25,000 – The 5 top-performing teams (on final leaderboard based on private test data) will receive $5,000 per team for travel award to attend the ECCV 2018 Conference.
Next important deadline:
July 30, 2018 - Entry deadline. You must accept the competition rules before this date in order to compete.
Join the competition
Good luck,
The Kaggle Team
منبع :
https://www.kaggle.com/c/youtube8m-2018?utm_medium=email&utm_source=intercom&utm_campaign=youtube+competition+2018
با کانال
https://news.1rj.ru/str/Machinelearning_Kartal/1361
همراه باشید
🌹انتخاب به عنوان کار تحقیقاتی جدید
🌿 انتخاب عنوان برای پایان نامه برای دوستان و دانشجویان ارشد عزیز.
💭برای بچه هایی که دنبال چالش و دنبال جایزه خوب
YouTube-8M Video Understanding Competition Launch: Create a Constrained-Size Model to Predict Video Labels
حامی اصلی این رقابت
Google AI
..🌹🌹🌹🌿🌿🌿🌹💭🌿
We've just launched the YouTube-8M Video Understanding Challenge! Here are the competition details. Click the button below if you're interested in competing, or digging deeper into the specifics.
Competition Denoscription:
This is the second Kaggle competition based on the YouTube 8M dataset, a large-scale video dataset that consists of millions of YouTube video features and associated labels from a diverse vocabulary of 3,700+ visual entities.
This year, the competition is focused on learning video representation under budget constraints. You’re challenge is to produce the best compact video classification model under 1GB.
YouTube
Host:
This competition is being hosted by Google AI (previously known as Google Research) as a part of the European Conference on Computer Vision (ECCV) 2018 selected workshop session.
Total prizes:
$25,000 – The 5 top-performing teams (on final leaderboard based on private test data) will receive $5,000 per team for travel award to attend the ECCV 2018 Conference.
Next important deadline:
July 30, 2018 - Entry deadline. You must accept the competition rules before this date in order to compete.
Join the competition
Good luck,
The Kaggle Team
منبع :
https://www.kaggle.com/c/youtube8m-2018?utm_medium=email&utm_source=intercom&utm_campaign=youtube+competition+2018
با کانال
https://news.1rj.ru/str/Machinelearning_Kartal/1361
همراه باشید
Kaggle
The 2nd YouTube-8M Video Understanding Challenge
Can you create a constrained-size model to predict video labels?
اگر شبکه عصبی عمیق خوبی طراحی کردی، در رقابتی که اندرواینگ گذاشته شرکت کنید...
https://stanfordmlgroup.github.io/competitions/mura/
با کانال
@Machinelearning_Kartal
هستید
https://stanfordmlgroup.github.io/competitions/mura/
با کانال
@Machinelearning_Kartal
هستید
وبینار رایگان برای شروع کار با ماشین لرنینگ با تنسورفلو روی پلتفرم ابرگوگل.
Get Started with Machine Learning with TensorFlow on Google Cloud Platform
Go behind the scenes of the new “Machine Learning with TensorFlow on Google Cloud Platform” specialization on Coursera, which will teach you how to build production-ready machine learning models. During this webinar, Lak Lakshmanan, Google Cloud Machine Learning expert, will preview some of the Machine Learning techniques you will learn, walk through a demo of how to debug TensorFlow programs, and share insights on the exciting field of Machine Learning. Register now and get free access to a Machine Learning lab to jumpstart your learning. All webinar attendees will also receive a free voucher to take the first course of the Coursera specialization for free.
Live online May 30 7:30 pm Germany - Berlin or after on demand 45 mins
منبع
https://www.brighttalk.com/webcast/10619/322293/get-started-with-machine-learning-with-tensorflow-on-google-cloud-platform
با کانال
https://news.1rj.ru/str/Machinelearning_Kartal/1362
همراه باشید
Get Started with Machine Learning with TensorFlow on Google Cloud Platform
Go behind the scenes of the new “Machine Learning with TensorFlow on Google Cloud Platform” specialization on Coursera, which will teach you how to build production-ready machine learning models. During this webinar, Lak Lakshmanan, Google Cloud Machine Learning expert, will preview some of the Machine Learning techniques you will learn, walk through a demo of how to debug TensorFlow programs, and share insights on the exciting field of Machine Learning. Register now and get free access to a Machine Learning lab to jumpstart your learning. All webinar attendees will also receive a free voucher to take the first course of the Coursera specialization for free.
Live online May 30 7:30 pm Germany - Berlin or after on demand 45 mins
منبع
https://www.brighttalk.com/webcast/10619/322293/get-started-with-machine-learning-with-tensorflow-on-google-cloud-platform
با کانال
https://news.1rj.ru/str/Machinelearning_Kartal/1362
همراه باشید
Brighttalk
Get Started with Machine Learning with TensorFlow on Google Cloud Platform
Go behind the scenes of the new “Machine Learning with TensorFlow on Google Cloud Platform” specialization on Coursera, which will teach you how to build production-ready machine learning models. Duri...