Deployed on AWS
    Image denoising solution for enhanced image clarity

    Overview

    This advanced image denoising solution presents a deeplearning based approach to the way noise is removed from digital images, leveraging the power of convolutional neural network model architecture to deliver exceptional results. This state-of-the-art solution effectively eliminates noise from custom images and ensures high-quality output. The solution is capable of preserving essential image details while removing unwanted noise, resulting in superior image clarity. To further enhance the denoising process, our solution incorporates bilateral filtering, a technique that smooths images while preserving edges. This advanced filtering method works in tandem with noise injection techniques to create a robust and comprehensive denoising solution.

    Highlights

    • The pre-trained model within our solution ensures that users can quickly and effectively denoise their images without the need for extensive training or fine-tuning. This out-of-the-box functionality makes our solution accessible to users of all skill levels and backgrounds.
    • This solution can be used for preprocessing images for any predictive analysis to improve the accuracy, portection against adeversarial attacks on the models and other computer vision related tasks in various industries like manufacturing, insurance, surveilance etc.
    • Need more machine learning, deep learning, NLP and Quantum Computing solutions. Reach out to us at Harman DTS.

    Details

    Delivery method

    Latest version

    Deployed on AWS

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    Features and programs

    Financing for AWS Marketplace purchases

    AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
    Financing for AWS Marketplace purchases

    Pricing

    Image Denoising

     Info
    Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
    Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator  to estimate your infrastructure costs.

    Usage costs (59)

     Info
    Dimension
    Description
    Cost/host/hour
    ml.m5.xlarge Inference (Batch)
    Recommended
    Model inference on the ml.m5.xlarge instance type, batch mode
    $50.00
    ml.t2.xlarge Inference (Real-Time)
    Recommended
    Model inference on the ml.t2.xlarge instance type, real-time mode
    $5.00
    ml.m4.4xlarge Inference (Batch)
    Model inference on the ml.m4.4xlarge instance type, batch mode
    $50.00
    ml.m5.4xlarge Inference (Batch)
    Model inference on the ml.m5.4xlarge instance type, batch mode
    $50.00
    ml.m4.16xlarge Inference (Batch)
    Model inference on the ml.m4.16xlarge instance type, batch mode
    $50.00
    ml.m5.2xlarge Inference (Batch)
    Model inference on the ml.m5.2xlarge instance type, batch mode
    $50.00
    ml.p3.16xlarge Inference (Batch)
    Model inference on the ml.p3.16xlarge instance type, batch mode
    $50.00
    ml.m4.2xlarge Inference (Batch)
    Model inference on the ml.m4.2xlarge instance type, batch mode
    $50.00
    ml.c5.2xlarge Inference (Batch)
    Model inference on the ml.c5.2xlarge instance type, batch mode
    $50.00
    ml.p3.2xlarge Inference (Batch)
    Model inference on the ml.p3.2xlarge instance type, batch mode
    $50.00

    Vendor refund policy

    We do not provide any usage related refunds at this time.

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    Legal

    Vendor terms and conditions

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    Usage information

     Info

    Delivery details

    Amazon SageMaker model

    An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.

    Deploy the model on Amazon SageMaker AI using the following options:
    Deploy the model as an API endpoint for your applications. When you send data to the endpoint, SageMaker processes it and returns results by API response. The endpoint runs continuously until you delete it. You're billed for software and SageMaker infrastructure costs while the endpoint runs. AWS Marketplace models don't support Amazon SageMaker Asynchronous Inference. For more information, see Deploy models for real-time inference  .
    Deploy the model to process batches of data stored in Amazon Simple Storage Service (Amazon S3). SageMaker runs the job, processes your data, and returns results to Amazon S3. When complete, SageMaker stops the model. You're billed for software and SageMaker infrastructure costs only during the batch job. Duration depends on your model, instance type, and dataset size. AWS Marketplace models don't support Amazon SageMaker Asynchronous Inference. For more information, see Batch transform for inference with Amazon SageMaker AI  .
    Version release notes

    Bug fixes and feature updates

    Additional details

    Inputs

    Summary

    Image file in PNG format

    Input MIME type
    image/png
    https://github.com/HDTS-user/LifewareAI-Image-Denoising/tree/main/input
    https://github.com/HDTS-user/LifewareAI-Image-Denoising/tree/main/input

    Support

    Vendor support

    Business hours email support marketplaceSupp@harman.com 

    AWS infrastructure support

    AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.

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