- Version 1.2
- Sold by Mphasis
This solution creates a 3D reconstruction from images using Structure-from-Motion (SfM) and Multi-View Stereo(MVS) techniques.
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.
This solution creates a 3D reconstruction from images using Structure-from-Motion (SfM) and Multi-View Stereo(MVS) techniques.
This is a NLP based solution that can be leveraged for any text classification problem to get the best model through AutoML training.
The solution provides occurrence and claim amount prediction for a policyholder. The solution is based on Regression and XG Boost.
Quantum Emulator based vehicle damage classifier is a Hybrid QML image classifier designed to detect damaged vehicle images.
ML based solution which classifies airline reviews into positive and negative sentiment categories.
Machine learning based customer complaint ticket triaging model to improve accuracy of ticket assignments and thereby improve FCR and MTTR.
An ML based solution to group a corpus of documents into clusters based on topics
The solution provides 24 hours forecast at an interval of 30 mins using historic network usage data.
The solution analyses customer characteristics to predict which customers are more likely to leave the bank.
The solution uses a classical regression approach to predict the number of customers churning in/out of a given insurance premium policy.
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