| 開發人員: | NEUROTECHNOLOGY UAB (4) | ||
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描述
On the app, users can immediately make predictions using a range of ready-to-use pre-trained models:
General Classification—. Use the General Classification pre-trained model to identify the content of your image. Classification is one of the primary uses of image recognition AI
General Object Detection—Using the pre-trained general object detection model allows users to identify what objects are in your image, along with the location of the object within the image.
Places Classification— Use the Places Classification pre-trained model to identify the place depicted in your image. The model provides a predicted score percentage.
NSFW Classification—The NSFW classification model can be used to detect whether images contain nudity or not. The model provides a prediction of whether the image is safe or unsafe, by way of a predicted score percentage.
Optical Character Recognition—The optical character recognition (OCR) pre-trained model can be used to detect and identify text within your image, and is supported for a wide variety of languages.
Pose Estimation—The pose estimation model can be used to detect the poses of people in the image. It detects 15 joints and key points of the human body.
Image Similarity Search—an image similarity search model is used to find visually similar images to one that is uploaded. The retrieved images are sorted by their similarity score.
With the SentiSight.ai mobile app, users can also make predictions using the custom models that have been trained using the SentiSight.ai web interface.
The app uses the same login credentials as the web version of SentiSight.ai.
The app does not currently support the training of new models itself, but the mobile app can be used to upload images to your projects that can be later used for training custom models.
The SentiSight.ai mobile app and web platform are developed by Neurotechnology. Neurotechnology is a developer of high-precision algorithms and software based on deep neural networks and other AI-related technologies. For more information about the company, please, visit the company’s website https://neurotechnology.com/
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