Detect file content types with deep learning

Collection of Keras models used for classification

Keras implementation of a ResNet-CAM model

Distributed Keras Engine, Make Keras faster with only one line of code.

K-CAI NEURAL API - Keras based neural network API that will allow you to create parameter-efficient, memory-efficient, flops-efficient multipath models with new layer types. There are plenty of examples and documentation.

Object classification with CIFAR-10 using transfer learning

Códigos Python com diferentes aplicações como técnicas de machine learning e deep learning, fundamentos de estatística, problemas de regressão de classificação. Os vídeos com as explicações teóricas estão disponíveis no meu canal do YouTube

We pit Keras and PyTorch against each other, showing their strengths and weaknesses in action. We present a real problem, a matter of life-and-death: distinguishing Aliens from Predators!

Classify movie posters by genre

Implemented two papers for offline signature verification. Both use different deep learning techniques - Convolutional network and Siamese network.

Classifying 10 different categories of Sound using Deep Learning.

Classification of Time-series data with RNN

Source code for the paper "Reliable Deep Learning Plant Leaf Disease Classification Based on Light-Chroma Separated Branches".

Make a graph network of your followers. Based on username and gender

RNN classifier built with Keras to classify MNIST dataset

Source code for the paper "Color-aware two-branch DCNN for efficient plant disease classification".

Multiple Handwritten Digit Recognition app Using Deep Learing - CNN from Canvas build on tkinter- GUI

QReLU and m-QReLU: Two novel quantum activation functions for Deep Learning in TensorFlow, Keras, and PyTorch

Detecting Brest Cancer from histology images using keras.

Identify and classify objects in real-time video streams using TensorFlow and OpenCV. This project is designed for applications like security systems, robotics, and interactive installations, combining the power of TensorFlow for deep learning with OpenCV's webcam interaction.