Artificial Intelligence in Android Development Artificial intelligence is the most exciting trend hitting the industry. From machines to mobile apps, the AI industry is expected to grow to $17 billion by 2020. AI in android app development works by making applications capable of learning and interacting very similar to humans. In essence, AI is supposed […]
Artificial intelligence is the most exciting trend hitting the industry. From machines to mobile apps, the AI industry is expected to grow to $17 billion by 2020.
AI in android app development works by making applications capable of learning and interacting very similar to humans. In essence, AI is supposed to make getting basic things done simple and accurate. The great thing about AI is that it doesn’t have to deal with the obstacles humans can face, such as emotional challenges and biased judgments. Thus, no flaws or mishaps in productivity or getting things done.
Industries all over, such as tourism and health care are incorporating AI. Also, Google has announced they’re shifting their goals to “A.I. First.”
New toolkits and programs for Android development have AI-based features, which allow for more AI development in android devices. The following are some of the features.
Thanks to deep learning, computers can detect and label things better than before by finding particular points in a image. This is improving apps with accurate face recognition and can help with other tasks such as automatic reading of radiology images.
This feature is the pathway for enterprise automation wherein both operational and strategic decision-making can be automated through AI. Image labeling in Android app development can label ground data in a collection of images or label a region of interests for use with object detection, pixel semantic segmentation and image classification.
Identifying or verifying a person from a video source has already been implemented as a feature to unlock smartphones and on Facebook to identify users in a photo. AI in facial recognition systems generally work by comparing facial features from a video source with faces in a database. Apps, in the near future, can possibly use face detection for types of surveillance or person/object tracking.
Text in images and videos can now be detected and recognized and used for stand-alone apps or combined with other mobile apps as an additional feature. Text can be recognized from any Latin-based language such as French, German, Dutch, Spanish and much more.