Deep learning channel pinned «لینک جدید گروه: https://t.me/joinchat/A3HTSj3_zWNXN0oApJf8rg»
PyRobot is a framework and ecosystem that enables AI researchers and students to get up and running with a robot in just a few hours, without specialized knowledge of the hardware or of details such as device drivers, control, and planning. PyRobot will help Facebook AI advance our long-term robotics research, which aims to develop embodied AI systems that can learn efficiently by interacting with the physical world. We are now open-sourcing PyRobot to help others in the AI and robotics community as well.
https://ai.facebook.com/blog/open-sourcing-pyrobot-to-accelerate-ai-robotics-research/
https://github.com/facebookresearch/pyrobot
https://www.pyrobot.org/
https://ai.facebook.com/blog/open-sourcing-pyrobot-to-accelerate-ai-robotics-research/
https://github.com/facebookresearch/pyrobot
https://www.pyrobot.org/
Meta
Open-sourcing PyRobot to accelerate AI robotics research
Facebook AI is open-sourcing PyRobot, a lightweight, high-level interface that lets AI researchers get up and running with robotics experiments in just hours, with no specialized robotics expertise.
List of the program committee of the Holistic Video Understanding Workshop in ICCV 2019:
Cees Snoek (UvA)
Mubarak Shah (UCF)
Jan van Gemert (TU Delft)
Ivan Laptev (INRIA)
Dima Damen (University of Bristol)
Du Tran (Facebook Research)
Hilde Kuehne (MIT-IBM Watson Lab)
Angela Yao (National University of Singapore)
Jakub Tomczak (Qualcomm AI Research)
Hakan Bilen (University of Edinburgh )
Noureldien Hussein (UvA)
Silvia-Laura Pintea (TU Delft)
Jack Valmadre (University of Oxford)
Suman Shah (ETH Zürich)
Efstratios Gavves (UvA)
Hamed Pirsiavash (UMBC)
Christoph Feichtenhofer (Facebook Research)
Chen Huang (Apple)
Makarand Tapaswi (INRIA)
Limin Wang (Nanjing University)
Tinne Tuytelaars (KU Leuven)
Saquib Sarfraz (KIT)
Yale Song (Microsoft Cloud & AI)
Miguel Angel Bautista (Apple)
David Ross (Google Research)
Sourish Chaudhuri (Google Research)
Chen Sun (Google Research)
Joao Carreira (Google Deepmind)
Andrew Owens (UC Berkley)
Basura Fernando (A*STAR Singapore)
Matt Feiszli (Facebook Research)
Philippe Weinzaepfel (NAVER Labs)
Josh Susskind (Apple)
Ross Goroshin (Google Brain)
https://holistic-video-understanding.github.io/workshops/iccv2019.html
Cees Snoek (UvA)
Mubarak Shah (UCF)
Jan van Gemert (TU Delft)
Ivan Laptev (INRIA)
Dima Damen (University of Bristol)
Du Tran (Facebook Research)
Hilde Kuehne (MIT-IBM Watson Lab)
Angela Yao (National University of Singapore)
Jakub Tomczak (Qualcomm AI Research)
Hakan Bilen (University of Edinburgh )
Noureldien Hussein (UvA)
Silvia-Laura Pintea (TU Delft)
Jack Valmadre (University of Oxford)
Suman Shah (ETH Zürich)
Efstratios Gavves (UvA)
Hamed Pirsiavash (UMBC)
Christoph Feichtenhofer (Facebook Research)
Chen Huang (Apple)
Makarand Tapaswi (INRIA)
Limin Wang (Nanjing University)
Tinne Tuytelaars (KU Leuven)
Saquib Sarfraz (KIT)
Yale Song (Microsoft Cloud & AI)
Miguel Angel Bautista (Apple)
David Ross (Google Research)
Sourish Chaudhuri (Google Research)
Chen Sun (Google Research)
Joao Carreira (Google Deepmind)
Andrew Owens (UC Berkley)
Basura Fernando (A*STAR Singapore)
Matt Feiszli (Facebook Research)
Philippe Weinzaepfel (NAVER Labs)
Josh Susskind (Apple)
Ross Goroshin (Google Brain)
https://holistic-video-understanding.github.io/workshops/iccv2019.html
A short note on "VideoBERT: A Joint Model for Video and Language Representation Learning"
By Chen Sun, Ausin Myers, @cvondrick, Kevin Murphy and Cordelia Schmid
https://twitter.com/yassersouri/status/1144283614953267201?s=19
By Chen Sun, Ausin Myers, @cvondrick, Kevin Murphy and Cordelia Schmid
https://twitter.com/yassersouri/status/1144283614953267201?s=19
Twitter
Yasser Souri
A short note on "VideoBERT: A Joint Model for Video and Language Representation Learning". https://t.co/fkKz2Fj9hC By Chen Sun, Ausin Myers, @cvondrick, Kevin Murphy and Cordelia Schmid (1)
A short note on "Deep Set Prediction Networks"
By: Yan Zhang et. al.
https://twitter.com/yassersouri/status/1146066000669896705
By: Yan Zhang et. al.
https://twitter.com/yassersouri/status/1146066000669896705
Twitter
Yasser Souri
Recently I read "Deep Set Prediction Networks" by Yan Zhang (@Cyanogenoid) et. al. https://t.co/8VW3yGhpOR This paper has received a lot of attention (deservedly) in the short time it has been published. (also @karpathy tweeted about it!) (1/14)
Forwarded from رویدادهای ملی و بین المللی
Amirkabir Artificial Intelligence Summer Summit (AAISS)
Advanced Topics in Machine Learning, Deep Leraning and, Neurosciences.
More information about Topics and Schedule coming soon...
Please inform your friends and colleagues
Follow us on social networks using #AAISS
#July2018
#Symposium #AI #Artificial_Intelligence #Machine_Learning #Machine_Vision #Speech #Deep_Learning #Neurosciences #AAISS
#Tehran #AUT #CEIT
@ceit_ssc
@convent
Advanced Topics in Machine Learning, Deep Leraning and, Neurosciences.
More information about Topics and Schedule coming soon...
Please inform your friends and colleagues
Follow us on social networks using #AAISS
#July2018
#Symposium #AI #Artificial_Intelligence #Machine_Learning #Machine_Vision #Speech #Deep_Learning #Neurosciences #AAISS
#Tehran #AUT #CEIT
@ceit_ssc
@convent
Forwarded from رویدادهای ملی و بین المللی
📌 ثبت نام سمپوزیوم تابستانه هوش مصنوعی امیرکبیر شروع شد. مباحث پیشرفته یادگیری ماشین، بینایی ماشین، پردازش صوت، یادگیری عمیق و علوم اعصاب
⚠️ ظرفیت ثبت نام محدود. مهلت ثبت نام تا یکشنبه 30 تیر 1398
🎓 همراه با پذیرایی و اعطای گواهی معتبر
🗓 1 تا 3 مرداد، آمفی تئاتر مرکزی دانشگاه صنعتی امیرکبیر
#مرداد1398
#July2019
#Symposium #AAISS
#Tehran #AUT #CEIT
aaiss.ceit.aut.ac.ir
@ceit_ssc
@convent
⚠️ ظرفیت ثبت نام محدود. مهلت ثبت نام تا یکشنبه 30 تیر 1398
🎓 همراه با پذیرایی و اعطای گواهی معتبر
🗓 1 تا 3 مرداد، آمفی تئاتر مرکزی دانشگاه صنعتی امیرکبیر
#مرداد1398
#July2019
#Symposium #AAISS
#Tehran #AUT #CEIT
aaiss.ceit.aut.ac.ir
@ceit_ssc
@convent
Holistic Large Scale Video Understanding - Towards Data Science
https://towardsdatascience.com/holistic-large-scale-video-understanding-c423701b777a
https://towardsdatascience.com/holistic-large-scale-video-understanding-c423701b777a
Medium
Holistic Large Scale Video Understanding
The topic of video content understanding is one of the most intriguing and challenging tasks in the computer vision field. Fortunately, …
Forwarded from رویدادهای ملی و بین المللی
🔗 هم اکنون، پخش زنده سمپوزیوم هوش مصنوعی امیرکبیر از طریق لینک زیر.
⚠️ توجه: در صورتی که برای اتصال با اینترنت شبکه های دانشگاهی مشکل داشتید از VPN استفاده کنید.
http://lahzenegar.com/ceit_ssc/live
https://t.me/convent/3840
@convent
⚠️ توجه: در صورتی که برای اتصال با اینترنت شبکه های دانشگاهی مشکل داشتید از VPN استفاده کنید.
http://lahzenegar.com/ceit_ssc/live
https://t.me/convent/3840
@convent
Lahzenegar
کاربر ceit_ssc - لحظهنگار
https://cvg-uni-bonn.github.io/cvg-paper-reading-group/
This reading group is focoused primarily on "Computer Vision" and "Machine Learning". Meetings are held in Informatik Institute III, University of Bonn, Germany.
This reading group is focoused primarily on "Computer Vision" and "Machine Learning". Meetings are held in Informatik Institute III, University of Bonn, Germany.
Forwarded from صرفا جهت اطلاع برنامهنویسان
☝️با توجه به اینکه گیت هاب داره حسابهای ایرانیها را بدون اخطار قبلی میبنده، توصیه میکنیم ریپازیتوریهاتون را دانلود کنید.
👈ریپو زیر هم لطفا استار کنید و دست به دست کنید. اگر هفتاد تا استار توی یه روز بخوره ترند میشه و دیده میشه و صدامون به یه جایی میرسه.
🔹https://github.com/1995parham/github-do-not-ban-us
#Github
🔹ارسالی از کاربر
〰️〰️〰️〰️〰️〰️
@programming_tips
👈ریپو زیر هم لطفا استار کنید و دست به دست کنید. اگر هفتاد تا استار توی یه روز بخوره ترند میشه و دیده میشه و صدامون به یه جایی میرسه.
🔹https://github.com/1995parham/github-do-not-ban-us
#Github
🔹ارسالی از کاربر
〰️〰️〰️〰️〰️〰️
@programming_tips
Talk - Dr Rahmani - Mordad 10 - 1398.pdf
61.8 KB
Talk - Dr Rahmani - Mordad 10 - 1398.pdf
Forwarded from پلیتکنیکیها
Media is too big
VIEW IN TELEGRAM
پخش گزارش «همایش هوش مصنوعی» دانشکده مهندسی کامپیوتر دانشگاه صنعتی امیرکبیر از برنامه «فوتون»
@Polytechnic1307
@Polytechnic1307
By incorporating more advanced training tasks, we've developed ERNIE 2.0, a continual pre-training framework for language understanding. The model built on this framework has outperformed BERT and XLNet on 16 #NLP tasks in Chinese and English.
http://research.baidu.com/Blog/index-view?id=121
http://research.baidu.com/Blog/index-view?id=121
Deep learning channel pinned «لینک جدید گروه: https://t.me/joinchat/A3HTSj3_zWNXN0oApJf8rg»
https://www.youtube.com/watch?v=iwcYp-XT7UI&t=2707s
George Hotz is the founder of Comma.ai, a machine learning based vehicle automation company. He is an outspoken personality in the field of AI and technology in general. He first gained recognition for being the first person to carrier-unlock an iPhone, and since then has done quite a few interesting things at the intersection of hardware and software. This conversation is part of the Artificial Intelligence podcast.
George Hotz is the founder of Comma.ai, a machine learning based vehicle automation company. He is an outspoken personality in the field of AI and technology in general. He first gained recognition for being the first person to carrier-unlock an iPhone, and since then has done quite a few interesting things at the intersection of hardware and software. This conversation is part of the Artificial Intelligence podcast.
YouTube
George Hotz: Comma.ai, OpenPilot, and Autonomous Vehicles | Artificial Intelligence (AI) Podcast
George Hotz is the founder of Comma.ai, a machine learning based vehicle automation company. He is an outspoken personality in the field of AI and technology...
The PhenoRob Project
The novel approach of PhenoRob is characterized by the integration of robotics, digitalization, and machine learning on one hand, and modern phenotyping, modeling, and crop production on the other. First, we will systematically monitor all essential aspects of crop production using sensor networks as well as ground and aerial robots. This is expected to provide detailed spatially and temporally aligned information at the level of individual plants, nutrient and disease status, soil information as well as ecosystem parameters, such as vegetation diversity. This will enable a more targeted management of inputs (genetic resources, crop protection, fertilization) for optimizing outputs (yield, growth, environmental impact). Second, we will develop novel technologies to enable real-time control of weeds and selective spraying and fertilization of individual plants in field stands. This will help reduce the environmental footprint by reducing chemical input. Third, machine learning applied to crop data will improve our understanding and modeling of plant growth and resource efficiencies and will further assist in the identification of correlations.
http://www.phenorob.de/wp-content/uploads/2017/03/cropped-phenorob.jpg
http://www.phenorob.de/
The novel approach of PhenoRob is characterized by the integration of robotics, digitalization, and machine learning on one hand, and modern phenotyping, modeling, and crop production on the other. First, we will systematically monitor all essential aspects of crop production using sensor networks as well as ground and aerial robots. This is expected to provide detailed spatially and temporally aligned information at the level of individual plants, nutrient and disease status, soil information as well as ecosystem parameters, such as vegetation diversity. This will enable a more targeted management of inputs (genetic resources, crop protection, fertilization) for optimizing outputs (yield, growth, environmental impact). Second, we will develop novel technologies to enable real-time control of weeds and selective spraying and fertilization of individual plants in field stands. This will help reduce the environmental footprint by reducing chemical input. Third, machine learning applied to crop data will improve our understanding and modeling of plant growth and resource efficiencies and will further assist in the identification of correlations.
http://www.phenorob.de/wp-content/uploads/2017/03/cropped-phenorob.jpg
http://www.phenorob.de/
