keras-classification-models
There are 211 repositories under keras-classification-models topic.
google/magika
Detect file content types with deep learning
titu1994/Keras-Classification-Models
Collection of Keras models used for classification
alexisbcook/ResNetCAM-keras
Keras implementation of a ResNet-CAM model
dkeras-project/dkeras
Distributed Keras Engine, Make Keras faster with only one line of code.
joaopauloschuler/k-neural-api
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.
alexisbcook/keras_transfer_cifar10
Object classification with CIFAR-10 using transfer learning
danmorales/CursoDS_ProfDanilo
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
deepsense-ai/Keras-PyTorch-AvP-transfer-learning
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!
benckx/dnn-movie-posters
Classify movie posters by genre
netrapathak/Offline-Signature-Verification
Implemented two papers for offline signature verification. Both use different deep learning techniques - Convolutional network and Siamese network.
swainshashwat/Audio-Classification-using-Deep-Learning
Classifying 10 different categories of Sound using Deep Learning.
AziziShekoofeh/Time-series-Classification
Classification of Time-series data with RNN
joaopauloschuler/two-path-noise-lab-plant-disease
Source code for the paper "Reliable Deep Learning Plant Leaf Disease Classification Based on Light-Chroma Separated Branches".
instautils/spider
Make a graph network of your followers. Based on username and gender
ar-ms/lstm-mnist
RNN classifier built with Keras to classify MNIST dataset
joaopauloschuler/two-branch-plant-disease
Source code for the paper "Color-aware two-branch DCNN for efficient plant disease classification".
luca-parisi/quantum_relu
QReLU and m-QReLU: Two novel quantum activation functions for Deep Learning in TensorFlow, Keras, and PyTorch
rkshiyaniya/Multiple-Handwritten-Digit-Recognition
Multiple Handwritten Digit Recognition app Using Deep Learing - CNN from Canvas build on tkinter- GUI
GiteshJ/Breast-Cancer-Phase-Detection
Detecting Brest Cancer from histology images using keras.
maghid/italian_fingerspelling_recognition
Dataset + convolutional neural network for recognizing Italian Sign Language (LIS) fingerspelling gestures
SandeepVashishtha/Image-Recognition
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.
aliemamalinezhad/Android-Malware-Detection
Android malware classification using both .java files and .so files
thakur-nandan/DeepLearningWithKeras
How to use the Keras Deep Learning library
Prajwal10031999/Cataract-Detection-using-VGG-19
A deep learning model built to detect cataract in human eyes using the VGG-19 pretrained weights
dhanushkamath/CIFAR-10
An IPython notebook demonstrating the process of Transfer Learning using pre-trained Convolutional Neural Networks with Keras on the popular CIFAR-10 Image Classification dataset.
sushantdhumak/Fashion-Clothing-Classification
Kaggle Machine Learning Competition Project : In this project, we will create a classifier to classify fashion clothing into 10 categories learned from Fashion MNIST dataset of Zalando's article images
asaldelkhosh/Pima-Indians
Implementing a keras model for diabetes recognition.
MoinDalvs/Neural_Networks_Forest_Fire_Classification
PREDICT THE BURNED AREA OF FOREST FIRES WITH NEURAL NETWORKS
scottherford/IDC_BreastCancer
Breast cancer is the most common form of cancer in women, and invasive ductal carcinoma (IDC) is the most common form of breast cancer. Accurately identifying and categorizing breast cancer subtypes is an important clinical task, and automated methods can be used to save time and reduce error. The goal of this script is to identify IDC when it is present in otherwise unlabeled histopathology images. The dataset consists of approximately five thousand 50x50 pixel RGB digital images of H&E-stained breast histopathology samples that are labeled as either IDC or non-IDC. These numpy arrays are small patches that were extracted from digital images of breast tissue samples. The breast tissue contains many cells but only some of them are cancerous. Patches that are labeled "1" contain cells that are characteristic of invasive ductal carcinoma. For more information about the data, see https://www.ncbi.nlm.nih.gov/pubmed/27563488 and http://spie.org/Publications/Proceedings/Paper/10.1117/12.2043872.
spatialaudio/classification_exercise
Multiclass classification example/exercise using deep neural networks (DNNs)
anjanatiha/Image-Recognition-using-Deep-Convolutional-Neural-Network
Image Recognition using Deep Convolutional Network and Training Pre-trained Models ("Inception")
officialpm/Face-Expression-Classification-CNN
🐵 Face Expression Classification using Convolutional-Neural Networks (CNN) 🔥 using fer2013 dataset 🚀
wikke/Kaggle-Dogs-vs-Cats
Dogs-vs-Cats image classification
easonlai/pneumonia_classification_challenge_databricks
This is sample repos for how to use Keras Tuner to perform hyper-parameter tuning in Databricks.
sdas2k18-tech/SRGANs
Super-resolution using GANs. CNN, Image Classification and Image Upscaling.
ShettySach/Kannada-Digit-Recognizer-v1
Using a Convolutional Neural Network (CNN) to identify the Kannada numerical digits. Tensorflow (Keras) is used to create, train and load the neural network model. CustomTKinter/TKinter are used to provide the GUI and OpenCV is used to read input form the GUI.