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androidtensorflowmachinelearningexample

Android TensorFlow MachineLearning Example (Building TensorFlow for Android)

androidtensorflowmnistexample

Android TensorFlow MachineLearning MNIST Example (Building Model with TensorFlow for Android)

bagofwords

Bag of words for image classification, a toy demo

bagofwords-1

Medical Image classification using bag of words model.

chinese-number-gestures-recognition

基于卷积神经网络的数字手势识别安卓APP，识别数字手势0-10（The number gestures recognition Android APP based on convolutional neural network(CNN), which can recognize the gestures corresponding number 0 to 10）

citrus-pest-classification-by-advanced-deep-learning

10 citrus pests classification, VGG-16, ResNet-50, Inception-ResNet-V3, Xception

cn-deep-learning

https://cn.udacity.com/course/deep-learning-nanodegree-foundation--nd101/

criteria3d

CRITERIA 3D provides a set of libraries and executables for agro-meteorological and climate analysis. It includes a numerical solution for three-dimensional water and heat flow in the soil, meteorological data interpolation, daily weather generator, radiation budget, snow accumulation and melt, plant development and plant water uptake.

grabcut-fcn

Improve the performance of traditional semi-automatic image segmentation algorithms (e.g. GrabCut) with U-Net

inception_based_cnn_model

基于Inception-v3实现的CNN分类模型

pneumonia-diagnosis-using-xrays-96-percent-recall

BEST SCORE ON KAGGLE SO FAR , EVEN BETTER THAN THE KAGGLE TEAM MEMBER WHO DID BEST SO FAR. The project is about diagnosing pneumonia from XRay images of lungs of a person using self laid convolutional neural network and tranfer learning via inceptionV3. The images were of size greater than 1000 pixels per dimension and the total dataset was tagged large and had a space of 1GB+ . My work includes self laid neural network which was repeatedly tuned for one of the best hyperparameters and used variety of utility function of keras like callbacks for learning rate and checkpointing. Could have augmented the image data for even better modelling but was short of RAM on kaggle kernel. Other metrics like precision , recall and f1 score using confusion matrix were taken off special care. The other part included a brief introduction of transfer learning via InceptionV3 and was tuned entirely rather than partially after loading the inceptionv3 weights for the maximum achieved accuracy on kaggle till date. This achieved even a higher precision than before.

scene-classify-bagofwords

tensorflow-tutorials

TensorFlow Tutorials with YouTube Videos

tensorflowclassification

train a image classifier

tensorflowtraining

TensorFlow Training For Android

tf

tensorflow examples

transferlearning

Everything about Transfer Learning and Domain Adaptation--迁移学习