Accenture Global Solutions Limited

Saurabh Mahadik

Chung-Sheng Li

Suraj Govind Jadhav

Madhura Shivaram

Guanglei Xiong

Emmanuel Munguia Tapia

Colin Connors

Mohammad Jawad Ghorbani

Kyle Patrick Johnson

Amioy Kumar

Nagendra K Kumar

Prakash Ghatage

Chinnappa Guggilla

Benjamin Nathan Grosof

Sumeet Sawarkar

Praveen Maniyan

Naveen Bansal

Karthik Meenakshisundaram

Nagendra Kumar M R

Christopher Cole

Sachin Aul

Sudhanshu A Dwivedi

Ankit Pandey

Hariram Krishnamurth

Karthik Lakshminarayanan

In some examples, image content moderation may include classifying, based on a learning model, an object displayed in an image into a category. Further, image content moderation may include detecting, based on another learning model, the object, refining the detected object based on a label, and determining, based on the another learning model, a category for the refined detected object. Further, image content moderation may include identifying, based on the label, a keyword associated with the object, and determining, based on the identified keyword, a category for the object. Further, image content moderation may include categorizing, based on a set of rules, the object into a category, and moderating image content by categorizing, based on aforementioned analysis the object into a category. Yet further, image content moderation may include tagging, based on fusion-based tagging, the object with a category and a color associated with the object.

Image content moderation

Systems and methods for orchestrating a process are disclosed. In an implementation, a system is configured to extract process information associated with the process. Based on the process information, the system is configured to determine a current model of performing the process based on the process information. The system is further configured to retrieve regulatory information associated with the process, wherein the regulatory information is indicative of at least one of a predefined policy, a predefined rule, and a predefined regulation associated with the process. Further, the system is configured to update the current model based on at least one of the process information and the regulatory information for obtaining a predefined outcome of the process.

Process orchestration

A curator captures input data corresponding to service tasks from an external source. Further, a browser extension collects intermediate service delivery data for the service tasks from the external source. Subsequently, a learner stores the input data and the intermediate service delivery data as training data. Then, a receiver receives a service request from a client. The service request is indicative of a service task to be performed and information associated with the service task. Further, an advisor processes the service request to generate an intermediate service response. Thereafter, the advisor determines a confidence level associated with the intermediate service response and ascertains whether the confidence level associated with service response is below pre-determined threshold level. If the confidence level is below a pre-determined threshold level, the advisor automatically generates a final service response corresponding to service request based on training data.

Integrated service centre support

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Mumbai, India

Saurabh Mahadik