302 skills found · Page 6 of 11
motlabs / Awesome Ml Demos With AndroidThe challenge for Tensorflow Lite and MLKit model inferencing on Android Platform
lijiancheng0614 / Android TFDetectAn android app using Tensorflow for Object Detection
ranitraj / InstaLensAndroid Mobile Application that uses camera to detect objects in real-time using TensorFlow Lite and implements additional UI functionalities.
shibuiwilliam / AI Ar OmochaPlaying Android with Tensorflow Lite, Firebase ML kit, and ARCore
nuaimat / GuessSketchGuess a Sketch - a project for Machine Learning class - using TensorFlow , python, Java and an Android App
arnabuchiha / SkinSense🎗 This is an Android app to detect melanoma skin cancer using tensorflow mobile.
lobrien / TensorFlow.Xamarin.AndroidXamarin bindings for the TensorFlow Android Inference library
sercant / Android Segmentation AppA basic Android application that runs semantic image segmentation using Tensorflow-Lite
dijorajsenroy / Skin Cancer Detection App3-layered approach to detecting cancer, melanoma and allergies with state-of-the-art Tensorflow models, integrated into an app with exciting features using Flutter Android development framework.
hiteshsahu / Android Machine Learning With TensorFlowTensor Flow implementation for Android
shhubhxm / Skin Disease Detection Team TechnophileWe are team technophiles and participated in 48hrs hackathon organized by Nirma University in collabration with Binghamton University. Our Problem Definition : To develop a solution, the first step is to understand the problem. The problem here is to develop an Application Programming Interface which can be easily integrated with Android and IOS to detect the skin disease without any physical interaction with a Dermatologist. The detected skin disease should be sent through whatsapp to a particular patient and doctor. Our college name: Pandit Deendayal Energy University Team Members: Rushabh Thakkar, Divy Patel, Denish Kalariya, Yug Thakkar, and Shubham Vyas. Project Details: We made an application which classifies the skin diseases into these given types healthy, lupus, ringworm and scalp_infections How did we make? The data given was analysed first. We came to conclusion that the data given was not enough so we searched for new datasets. We got these datasets: https://ieee-dataport.org/documents/image-dataset-various-skin-conditions-and-rashes https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/DBW86T We segregated the datasets of harvard. Combined all the datasets and trained the tensorflow image classification model multiple times. Accuracy was not satisfying. Augmented the data to unbaised the model and the dataset would be balanced. Data Augmentation was done on the data given . We generated 800 images per disease. Again we had trained the model. Accuracy was good. Exported the .tflite and label.txt file. We imported the files into android studio We have used three python codes: data_removal.py This code is used to remove data randomly from the folder if there are more number of images than required. We just need to change total_files_req variable in the code to number of files required after deletion. data_augmentation.py This code is used to augment the data randomly from the folder if there are less number of images than required. We just need to change total_files_req variable in the code to number of files required after augmentation. We change various parameters of images like clearity, rotation, brightness, etc. image_classification_code.py This is the main code in which we have trained the model and exported it to run on the app Models we tried: efficientnet-lite0(USED in our project) efficientnet-lite1 efficientnet-lite2 efficientnet-lite3 efficientnet-lite4 API: TensorFlowLite Used Android studio for App development . Used Language = java We sync all the grade files. Changed the model files and update it with the new model Working model file name is model.tflite Tflite classifier working java files are CameraActivity.java CamerConnectionFragment.java ClasssifierActivity.java LegacyCameraConnectionFreagment.java Dataset: Uploaded on Github WORKING MODEL LINK: https://drive.google.com/file/d/1BnqfFInFkJJDkYDlmdj9VB601f7PjTdj/view?usp=sharing
GehenHe / Recognize Face On AndroidThis is an Android face recognize application that based on tensorflow , you can develop it with Android Studio
arefbhrn / IRDebitCardScannerIranian debit card (credit card) real-time scanner using Deep Learning and TensorFlow Lite for Android.
codewith-pk / Deepseek AI For AndroidIntegrating the DeepSeek AI model into Android apps. It covers the process of downloading the model from Hugging Face, converting it to ONNX, TensorFlow, and TensorFlow Lite formats, and using it in an Android app with an interactive chat interface built using Jetpack Compose.
Jyotsna-Shetty / VehicleInfoCheckAndroid application for Indian license plate recognition using deep learning (Tensorflow) and OpenCV, and extraction of vehicle details from the Vahan website.
GuidoPaul / Android Tensorflow Style TransferBased on tensorflow's style transfer Android project.
NSTiwari / Cartoon Classification On Android Using TF LiteA fun image classification Android app that classifies cartoons using TensorFlow Lite.
ddxxll2008 / PoseNetOnAndroid仿照HomeCourt App写一个Android版本，使用的是Google的tensorflow lite的PoseNet模型
nicolefinnie / TFdetectA stand-alone Android app from Tensorflow TF detect with Yolo V2 coco
wentaibao / FaceRecognitionAndroid端通过TensorFlow模型完成人脸识别与相似度对比
