CNN analysis for Accept_Reject Pooling and Stochastic Pool
1. the goal of the project is to make use of two custom layers,from publications - Accept Reject Pooling and Stochastic Pooling layer and compare its performances. 2. The layers were implemented into Keras models and used to train MNIST, CIFAR 10 and CIFAR 100 datasets. 3. The implementation was done with keras with tensorflow backend and jupyter notebook.
Om mig
I primarily focus on perfection, or create and do things by giving my best! My motto, Live and do your best every second :). My passionate interests are Embedded, Robotics, Machine Vision, NLP, ML and Neural networks. I also work with android app development. Languages skilled : 1. python (theano/tensorflow/keras/caffe/sklearn/pandas/numpy/scipy/django/beautifulsoup4/selenium) 2. Matlab 3. C/c++ Packages : 1. Tesseract 2. Opencv 3. ocropy 4. ALPR Applications: 1. OCR 2. ANPR - Automatic Number Plate Recognition 3. Object Recognitions 4. Image classifications 5. Forecasts and prediction models. 6. Stock and Forex forecasts / predictive analysis.
