Tag Archives: Artificial Neural Networks

1D-CNN based Fully Convolutional Model for Handwriting Recognition

Handwriting

Handwriting Recognition also termed as HTR(Handwritten Text Recognition) is a machine learning method that aims at giving the machines an ability to read human handwriting from real-world documents(images). The traditional Optical Character Recognition systems(OCR systems) are trained to understand the variations and font-styles in the machine-printed text(from documents/images) and they work really well in practice(example-Tesseract). Handwriting Recognition on… Read More »

Optimizing TensorFlow models with Quantization Techniques

https://www.codesofinterest.com/2019/10/tensorflow-20-released.html

Deep Learning models are great at solving extremely complex tasks efficiently but this superpower comes at a cost. Due to a large number of parameters, these models are typically big in size(memory footprint) and also slow in the inference (during predictions). Slow and heavy models are not much appreciated when it comes to the deployment part. As we… Read More »

Deep Learning with PyTorch: First Neural Network

PyTorch: neural netoworks

Deep Learning is part of the Machine Learning family that deals with creating the Artificial Neural Network (ANN) based models. ANNs are used for both supervised as well as unsupervised learning tasks. Deep Learning is extensively used in tasks like-object detection, language translations, speech recognition, face detection, and recognition..etc. Let’s create our First Neural Network with PyTorch- In… Read More »