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Google is releasing a new TensorFlow object detection API to make it easier for developers and researchers to identify objects within images. Google is trying to offer the best of simplicity and ...
Google Lens is an image recognition technology developed by Google, designed to bring up relevant information related to objects it identifies using visual analysis based on a neural network. [2] First announced during Google I/O 2017, [ 3 ] it was first provided as a standalone app, later being integrated into Google Camera but was reportedly ...
Google Assistant, in the nature and manner of Google Now, can search the Internet, schedule events and alarms, adjust hardware settings on the user's device, and show information from the user's Google account. Unlike Google Now, however, the Assistant can engage in a two-way conversation, using Google's natural language processing algorithm.
It is a replacement for the Eclipse Android Development Tools (E-ADT) as the primary IDE for native (local) Android application development. Android Studio is licensed under the Apache license but it also ships with some SDK updates that are under a non-free license, making it not an open source. [10]
Small object detection is a particular case of object detection where various techniques are employed to detect small objects in digital images and videos. "Small objects" are objects having a small pixel footprint in the input image. In areas such as aerial imagery, state-of-the-art object detection techniques under performed because of small ...
Objects detected with OpenCV's Deep Neural Network module (dnn) by using a YOLOv3 model trained on COCO dataset capable to detect objects of 80 common classes. Object detection is a computer technology related to computer vision and image processing that deals with detecting instances of semantic objects of a certain class (such as humans, buildings, or cars) in digital images and videos. [1]
The Android SDK is a software development kit for the Android software ecosystem that includes a comprehensive set of development tools. [ 2 ] [ 3 ] These include a debugger , libraries , a handset emulator based on QEMU , documentation, sample code, and tutorials.
All detection techniques are based on modelling the background of the image, i.e. set the background and detect which changes occur. Defining the background can be very difficult when it contains shapes, shadows, and moving objects. In defining the background, it is assumed that the stationary objects could vary in color and intensity over time.
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