With camera-equipped modern gadgets and smartphones, image recognition is in high demand in various spheres both for industrial and consumer applications. Despite the fact that humans perform object recognition tasks almost unconsciously, computer image recognition process require high-quality programming and lots of processing power to recognize objects accurately.
However, our R&D engineers accepted the challenge and adopted a convolutional neural network model proposed by the University of Oxford due to our needs and successfully delivered the prototype for processing images with different types of kitchen furniture and appliances in them and naming the objects present in these pictures. So-called image annotation process is successfully applied in this case.
Although such a ready-to-use software solution, especially one that will provide a high production-level accuracy, is unlikely to be found on the market today, our experts share their results with you. Try out the algorithm by yourself and share your feedback with us!
It can be used to simplify and improve overall search results benefit in terms of data loss, timespan and human resources.
It can be applied to any other sphere that require specific objects recognition and image annotation.
The algorithm can process frames from your camera in real time.
The algorithm is able to detect the objects even on low resolution images.
Choose one of the sample images or upload your own image with any of the following kitchen objects: dining table, stove, microwave oven, dishwasher, washing machine, refrigerator, plate rack, waffle iron, espresso maker, cocktail shaker.