CASE STUDY

Facial and Emotion Recognition

THE CHALLENGE

Train and enhance the system’s cognition capabilities based on the inputs, and customize it to CRM application use-cases

OVERVIEW OF

Our Solution

Cientra built an image recognition application using Cognitive framework to train the system to learn with each facial image added into the repository. We enhanced the system’s emotion recognition engine to detect demographic information such as age and gender, and other elements such as spectacles, beards, etc.
TECHNOLOGIES

Watson Visual Recognition

Quickly and accurately tag, classify and train visual content using machine learning.

ALL DOMAINS

Semiconductors

Architecting feature-rich chipsets in the digital, analog and mixed signal space.

Wireless

Developing and testing communication protocols across radio access and core networks.

Platforms

Building firmware and cross-OS porting capabilities for embedded architectures.

Automotive

Achieving seamless mobility through co-existence of ECU applications, data analytics and AI.

AI & Gaming

Combining the power of ML bots, image recognition and NLP into smart enterprise and consumer applications.

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