Neural network usage usually takes a lot of computations, but in our modern world, even a smartphone can be a device to run your trained neural model. Today we will take a look at how we can convert a ...
Playing Rock, Paper, Scissors with AI
Let’s play rock, paper scissors.You think of your move and I’ll make mine below this line in 1...2…and 3. I choose ROCK. Well? ...who won. It doesn't matter cause you probably glanced at the ...
CNN Receptive Field Computation Using Backprop with TensorFlow
In our recent post about receptive field computation, we examined the concept of receptive fields using PyTorch. We learned receptive field is the proper tool to understand what the network 'sees' ...
CNN Fully Convolutional Image Classification (FCN CNN) with TensorFlow –
In a previous post, we covered the concept of fully convolutional neural networks (FCN) in PyTorch, where we showed how we could solve the classification task using the input image of arbitrary ...
How to Convert a Model from PyTorch to TensorRT and Speed Up Inference
The life of a machine learning engineer consists of long stretches of frustration and a few moments of joy! First, struggle to get your model to produce good results on your training data. You ...
Efficient image loading
When it comes to writing optimized code, image loading plays an important role in computer vision. This process can be a bottleneck in many CV tasks and it can often be the culprit behind bad ...
