Consider checking out this Amazing tutorial series on AI and Machine learning on YouTube.

#machinelearning #artificialintelligence #deeplearning #python #computervision

https://lnkd.in/eui_KjZ

AI and Machine Learning Part 1 of 4

✴️ @AI_Python_EN

Exercise safely with AI and Computer Vision

In partnership with University of Zurich, startup VAY has just created a new way to coach fitness, using Artificial Intelligence and Computer Vision. The app called "Vay Sport" helps to avoid injuries and improve performance while training. It observe the exercises and provides real-time feedback on posture during workouts

Thanks to deep learning, the App instantly creates a computer model of the human body to read out joint angles and limb positions.
The algorithm was developed with certified coaches to recognize optimal exercise execution

Read more here: https://lnkd.in/fM9WmmN

#deeplearning #computervision #artificialintelligence #training #fitness #innovation #technology

✴️ @AI_Python_EN

Don't mess with Robots! 😂😂

#robots #robotics #ai #artificialintelligence #machinelearning #deeplearning #datascience #dataanalytics #bigdata #computervision #automation #technology #innovation #emergingtechnologies

Bosstown Robotics

✴️ @AI_Python_EN

I am implementing a training loop that can be used with Auxiliary Classifier. So what is an Auxiliary Classifier?

Auxiliary Classifier are the ones in which we take the outputs of layers of some previous layers along with the final outputs and compare it with the targets and calculate a loss based on both the outputs from the final layer as well as the previous layer.

How does this help?
I think before even me saying how this is going to be helpful, I think this intuitively gives an idea of how is this going to aid the training process, I got so freaking excited when I came to know about this.

So, How does this help?
- Solves the gradient Vanishing problem
- Low-level features get more and more accurate and thus making the model more and more accurate.
- This also acts as regularization, it kind of can be thought as putting some constraints on the model which help in regularization.

I am not sure which paper first introduced Auxiliary Approaches, but I am trying to train an FCN using this, let's see how this aids the process :)
Maybe the Inception paper.

#machinelearning #deeplearning #datascience #python #artificialintelligence #selfdriving #nlp #computervision

✴️ @AI_Python_EN

Using Neural Networks to perform makeup.
#neuralnetwork #ComputerVision
#Artificialntelligence

https://medium.com/mathematical-beauty/deep-learning-for-cosmetics-2d1b427bbfa2

✴️ @AI_Python_EN

Releasing STEAL, a new semantic boundary detector that significantly outperforms past work. Use STEAL to refine segmentation datasets, and train better segmentation models!
paper:https://arxiv.org/abs/1904.07934
code:https://github.com/nv-tlabs/STEAL
#computervision
✴️ @AI_Python_EN

Capturing Context in Emotion AI: Innovations in Multimodal Video Sentiment Analysis
#ComputerVision #MachineLearning #ArtificialIntelligence

http://bit.ly/2ZdU6yc

✴️ @AI_Python_EN

1000x Faster Data Augmentation

#ComputerVision #MachineLearning #ArtificialIntelligence

http://bit.ly/31hpcH0
✴️ @AI_Python_EN

Dr. Andrew Fitzgibbon is an expert in 3D #computervision and graphics. Discover work on body- and hand-tracking for tech like Kinect and HoloLens and hear how research on dolphins helped build models for the human hand:
https://aka.ms/AA5b1q9 #CVPR2019
✴️ @AI_Python_EN

How to make a pizza: Learning a compositional layer-based GAN model. Or “MIT’s AI learns to Become Pizza Guru. All pizza design will soon be automated. ”
https://arxiv.org/abs/1906.02839
#gan #ai #computervision

✴️ @AI_Python_EN

Check out Scene Representation Networks:
https://youtu.be/6vMEBWD8O20
new continuous 3D-aware scene representation reconstructs appearance and geometry just from posed images, generalizes across scenes for single-shot reconstruction, and naturally handles non-rigid deformation!
https://arxiv.org/abs/1906.01618
#computervision

✴️ @AI_Python_EN

All the datasets (there are a lot) released at #cvpr2019 are now indexed in
http://visualdata.io . Check them out!
#computervision #machinelearning #dataset

✴️ @AI_Python_EN

TensorFlow 2.0 Beta has just been released!! This time, I am a big fan. The new version is so good, so easy & intuitive, and game changing compared to the previous TensorFlow 1 versions. It has such massive value that I decided to make a huge course on TensorFlow 2.0, covering most of the useful models in Deep Learning and Artificial Intelligence. Seriously this is one of the most complete guides I’ve ever made: inside we implement ANNs, CNNs, RNNs, Deep Q-Learning, Transfer Learning, Fine Tuning, APIs for Mobile Apps, Computer Vision, Deep NLP, Data Validation, TensorFlow Extended and even Distributed Training handling multiple GPUs, all that in TensorFlow 2.0!

And that’s not all, during these first 72 hours you get three amazing Bonuses, including the highly demanded Yolo v3, one of the most powerful models in Computer Vision.

Link here:
https://lnkd.in/gBtZuMN

#machinelearning #deeplearning, #artificialintelligence #computervision #nlp #completeguide
✴️ @AI_Python_EN

Convolutional #NeuralNetworks (CNN) for Image Classification — a step by step illustrated tutorial: https://dy.si/hMqCH
BigData #AI #MachineLearning #ComputerVision #DataScientists #DataScience #DeepLearning #Algorithms

✴️ @AI_Python_EN