Invention Publication
- Patent Title: IMAGE QUANTIZATION USING MACHINE LEARNING
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Application No.: US17546391Application Date: 2021-12-09
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Publication No.: US20230186429A1Publication Date: 2023-06-15
- Inventor: Mohammad Sadegh NOROUZZADEH , Renan Alfredo ROJAS GOMEZ , Anh NGUYEN , Filipe J. CABRITA CONDESSA
- Applicant: Robert Bosch GmbH
- Applicant Address: DE Stuttgart
- Assignee: Robert Bosch GmbH
- Current Assignee: Robert Bosch GmbH
- Current Assignee Address: DE Stuttgart
- Main IPC: G06T3/40
- IPC: G06T3/40 ; G06N3/08 ; G06T7/90

Abstract:
Methods and systems are disclosed for quantizing images using machine-learning. A plurality of input images are received from a sensor (e.g., a camera), wherein each input image includes a plurality of pixels. Utilizing an image-to-image machine-learning model, each pixel is assigned a new pixel color. Utilizing a mixer machine-learning model, each new pixel color is converted to one of a fixed number of colors to produce a plurality of quantized images, with each quantized image corresponding to one of the input images. A loss function is determined based on an alignment of each input image with its corresponding quantized image via a pre-trained reference machine-learning model. One or more parameters of the image-to-image machine-learning model and the mixer model are updated based on the loss function. The process repeats, with each iteration updating the parameters of the image-to-image machine-learning model and the mixer model, until convergence, resulting in trained models.
Public/Granted literature
- US11893709B2 Image quantization using machine learning Public/Granted day:2024-02-06
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