Android Developer Challenge The Winning Apps Powered By Ml

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Finding the right words faster in Gmail. Helping you pick the most popular dish on a menu with Google Lens. Automatically captioning videos or podcasts on your Android phone with Live Caption. What do all of these features have in common? They use Google’s machine learning to help you get things done faster and easier throughout your day.
This technology is becoming more accessible to the developers who build the apps you use everyday. To encourage more developers around the world to build apps using machine learning, we launched the Android Developer Challenge last year. And after months of hard work, today the 10 winners of the Android Developer Challenge are launching their apps ready for you to try out. Each of these projects was created by the developers individually not Google:

AgriFarm helps farmers detect plant diseases and prevent major damage in fruits and vegetables such as tomatoes, corn and potatoes. [Balochisan, Pakistan]AgroDoc helps farmers diagnose plant disease and make treatment plans. [Navneet Krishna; Kochi, India]Eskke simplifies mobile money management for people in the Congo, letting them transfer money, pay bills, and buy subscriptions and essential airtime for sending SMS. [David Mumbere Kathoh; Goma, Democratic Republic of Congo]Leepi helps students learn hand gestures and symbols for American Sign Language. [Prince Patel; Bengaluru, India]MixPose is a live streaming app that gives yoga teachers and fitness professionals the opportunity to teach, track alignment, make sure you’re in the correct pose, and give real-time feedback. [Peter Ma; San Francisco, California, USA]Pathfinder could help people with visual impairments navigate complex situations by identifying and calculating the trajectories of objects moving in their path. [Colin Shelton; Addison, Texas, USA]Snore & Cough helps you identify and analyze snoring and coughing, so you can listen to and send recordings from a night’s sleep. [Ethan Fan; Mountain View, California, USA]Stila pairs with a wearable device, like the Fitbit wristband or a device running on Wear OS by Google, to monitor, track and help manage the body’s stress levels. [Yingdin Wing; Munich, Germany]Trashly makes recycling easier. Just point the on-device camera at an item, and through object detection, the app identifies and classifies plastic and paper cups, bags, bottles, etc. [Elvin Rakhmankulov; Chicago, Illinois, USA]UnoDogs helps owners better support their pet’s wellness, providing customized information and fitness programs. [Chinmany Mishra; New Delhi, India]
Agrifarm.pngAgro.pngEskke.pngLeepi.pngMP.pngPath Finder.pngSnoreandCough.pngStila.pngTrashly.pngUnodogs.pngYou can learn more about all of these winners, and the Google technologies behind these apps. There's still so much potential when it comes to machine learning, and developers will help us uncover it.

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