- Version 3.0
- Sold by Mphasis
Computer Vision & ML based Printed Circuit Board defect detector for missing hole, mouse bite, spur, open/short circuit and spurious copper
Mphasis applies next generation technology to help enterprises transform businesses globally. Customer centricity is foundational to Mphasis and is reflected in the Mphasis FrontBack™ Transformation approach. 'Front2Back' uses the exponential power of cloud and cognitive to provide hyper-personalized digital experience to clients and their customers. Mphasis Service Transformation approach helps 'shrink the core' through application of digital technologies across legacy environments within an enterprise, enabling businesses to stay ahead in a changing world.
Computer Vision & ML based Printed Circuit Board defect detector for missing hole, mouse bite, spur, open/short circuit and spurious copper
Deep Learning powered classification solution generates insights from highly skewed data with relevant class (e.g. fraud cases) < 1% of data
This solution can estimate the performance of a machine learning model in production without access to class lable and detect data drift.
The solution provides 60 minutes forecast of the network traffic using historic data.
The solution provides 30 months forecast of Inventory using historical monthly Inventory data.
The solution performs automated feature engineering steps like feature selection and can remove rare levels from features.
This solution provides explanations for the predictions of a user-provided image classification model on their datasets.
Given a scanned document, this deep-learning solution enhances the document quality by removing unwanted elements like dots, lines, smudges.
A deep learning based solution that extracts insights in response to the factoid questions with respect to the context passage.
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