Amateur food photography has risen in tandem with the rise of Instagram, and the Lose It app is capitalizing on social media users' love for snapping their meals. The dieting app tracks users meals, and its new photography feature makes it easier and quicker than ever to stay on top of their diets.
Lose It's new feature is called 'Snap It,' and it works just like taking a food picture on Instagram. Through the app, users can use their smartphone cameras to take a picture of whatever their meal is. But, rather than sending this image out onto a social network, the app uses a neural network to process the image and analyze what type of food it is. According to the Lose It website, Snap It is approximately 87 percent accurate with its predictions.
Photographic Meal-Tracking Apps
'Lose It' Logs Users' Meals By Registering Their Pictures
Trend Themes
1. Amateur Food Photography - Lose It app capitalizes on the rise of Instagram and amateur food photography by offering a photography feature to track users' meals.
2. Dieting Apps - Lose It app's 'Snap It' feature introduces a disruptive innovation in dieting apps by using neural networks to analyze food images and track users' diets.
3. Food Image Recognition - Lose It app's 'Snap It' feature relies on advanced image recognition technology to accurately identify and categorize different types of food from user photos.
Industry Implications
1. Health and Fitness - Lose It app's new photography feature presents disruptive innovation opportunities in the health and fitness industry by providing an easy and efficient way for users to track their meals.
2. Mobile App Development - Lose It app's use of neural networks for food image analysis opens up disruptive innovation opportunities in the mobile app development industry, particularly in the realm of dieting and nutrition applications.
3. Artificial Intelligence - Lose It app's integration of neural networks and image recognition technology highlights disruptive innovation opportunities in the artificial intelligence industry, particularly in the field of food analysis and dietary tracking.