Advanced deep learning learning techniques, layers, activations loss functions, all in keras / tensorflow

Fast and accurate AI powered file content types detection

All about creating a dataset, preprocessing images, and creating an actual model to solve captcha

Serving a keras model (neural networks) in a website with the python Django-REST framework.

A Keras port of Detector of Rotatable Bounding Boxes

A deep learning model designed for sentiment analysis by leveraging the power of ResNet and GoogleNet-inspired architectures. This hybrid model efficiently extracts high-level semantic features from textual data to classify sentiments into Positive, Negative, or Neutral categories.

An Image Recognition AI tool, which is use to show the number on a picture. (0~9 only) TEST Accuracy: 0.97

An easy, simple and reprogrammable AI chatbot using tensorflow and keras with a handful of training data.

Detecting Dormice in Images Using Object Detection and Transfer Learning

An implementation of Graph Convolutional Neural Networks (GCNN) using TensorFlow

DDIM implementation for superresolution

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

Basis CNN intro& project of recognize to cat or dog

Segmentation models with pretrained backbones. Keras and TensorFlow Keras.

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.