Deep learning solutions for an oil and gas company

Solutions

With the collaborative and consultative approach of our data scientists, we worked closely with the client to understand their unique business needs. After thoroughly discussing their pain points, we offered them deep learning solutions.

Data Preprocessing and feature extraction

SageMaker was utilized to preprocess and clean the data, ensuring its readiness for analysis. It provided tools for data transformation, feature engineering and dimensionality reduction, preparing the data for the YOLO algorithm. By utilizing SageMaker’s capabilities, the data was appropriately formatted and optimized for the subsequent computer vision tasks.

Model training and optimization

We leveraged SageMaker to train and optimize the YOLO algorithm. It provided a managed environment for training the computer vision model at scale, using the client’s labeled data. Our data engineers trained the YOLO model SageMaker’s distributed computing resources.

Deep learning solution for automated error detection

Softweb Solutions implemented an automated error detection system using the YOLO V3 algorithm. It is a state-of-the-art object detection system that uses deep neural networks to identify objects in images and videos. This provided the client with an automated system that detects and highlights errors in their documents.

The implementation of this error detection system provided our client with a highly efficient and time-saving solution. By simply adding the details of the document into a user-friendly form, the algorithm takes over and meticulously scans the entire document for errors. Any identified errors are promptly highlighted, enabling the client to swiftly identify and rectify them. This not only ensures the integrity and accuracy of the data but also reduces the risk of circulating erroneous information.