International Business Machines Corporation

Prakriti Pritmani

Aakash Praliya

Jenny S Li

Nancy Anne Greco

Nirmit V Desai

Tova Roth

Luis Angel Bathen

Dhiraj Joshi

Wei-Han Lee

Gwilym Benjamin Lee Newton

Sujoy Kumar Roy Chowdhury

Sridhar Jonnala

Saigeetha Aswathnarayanan Jegannathan

Shiva G

Kay Murphy

Shilpa Shenai

Arun Yashwant Ingale

Raghu Ramaswamy

Ajjay Ratnakar

Venkata Jami

Harsha Deuri

Satish Rajani

Dynamically adjusting, using artificial intelligence (AI), sensors and models of an autonomous roaming robotic device, which includes receiving data regarding an asset at a computer of a roaming robotic device from sensors on the robotic device. The robotic device identifies an asset at a location using the sensors, and the robotic device has instructions, received from a control system, to inspect the location or items at the location. The data is analyzed using the computer of the robotic device, and the analysis includes using historical data for the asset. An AI model is loaded using the computer of the robotic device, based on the identification of the asset. A sensor is selected using the computer of the robotic device, for conducting an inspection of the asset based on the analysis of the data and the AI model.

Dynamic use of artificial intelligence (AI) models on an autonomous AI enabled robotic device

A method for automatically enhancing image data comprising receiving image data. Utilizing a neural network to analyze the image data to predict how each of a plurality of image enhancement processes will affect the image data. Utilizing the neural network to calculate a reward value for each of the plurality of enhancement processes that can be applied to the image data. Determining if the image data should be enhanced or not, wherein the determination is based on the predictions how each of the plurality of image enhancement processes will affect the image data. When it is determined that the image data should be enhanced, then determining which of the plurality of image enhancing process should be applied to the image data, wherein determination is based on the reward value for each of the plurality of enhancement processes. Applying the determined enhanced processes to the image data.

System and method of automatic image enhancement using system generated feedback mechanism

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Ahmedabad, India

Prakriti Pritmani