When I read deep learning papers, I often think that describing neural net architectures in code (or pseudocode) is much more useful than using detailed, 3D rendered diagrams of architectures. Best to have both:
Today we are sharing a color detection, segmentation application: Potter's Invisibility Cloak, by Kaustubh Sadekar.
https://t.co/K2MqPymET4
We are sharing the code in both C++ and Python. If you like it, please retweet.
#AI#MachineLearning#DeepLearning#OpenCV#LearnOpenCV
This is a super cool resource: Papers With Code now includes 950+ ML tasks, 500+ evaluation tables (including SOTA results) and 8500+ papers with code. Probably the largest collection of NLP tasks I've seen including 140+ tasks and 100 datasets.
https://t.co/lTAGE7LGZY
Checkout the @Pentaho#CDE real-time dashboard work that Paulo has done with the #LiDAR and #Particulate sensor data stream challenge at https://t.co/qy3uxqfwZR. Really cool work. Keep it up. Read more at https://t.co/0fdP7M9WYQ with @HitachiVantara Labs
Check out some new robotics research that addresses unsupervised learning of depth and ego-motion from a monocular camera, tackling the problem of highly dynamic scenes while achieving results comparable to stereo camera sensors. It's open source too! https://t.co/yctankNOQw
We are releasing a @TensorFlow package for the Active Question Answering (ActiveQA) research project we introduced at #ICLR2018. Learn how you can build your own ActiveQA system by visiting the Google AI blog at https://t.co/IelMf84r7g.
Entusiastas de BI que residem nas cidades e regiões próximas a Curitiba (30/11 e 01/12) e Brasília (03/12 e 04/12), em breve estarei em suas cidades com o "Workshop Avançado de BI com Pentaho Community" by BovBI.
Maiores informações no link: https://t.co/xVe5I1JJav
A high school student made a deep learning library to help him understand how neural networks work. He implemented vanilla fully connected, conv, pooling layers, GRU cells, various gradient descent optimizers & other cool stuff like a Keras-like interface. https://t.co/8ITrgRoxc4
Building ML models that are robust and inclusive even when learning from imperfect data is an important research challenge. To spur further progress in developing inclusive models, we are announcing the Inclusive Images Competition on Kaggle. https://t.co/gVMImMZ8sR