Sold by: MphasisÂ
Deployed on AWS
Image analytics-based solution to classify salient surface defects in screw fastener heads.
Overview
Surface defects in screw fastener heads pose quality and performance risks. Classifying defects enables for the rapid identification and removal of the causes of their occurrence, as well as the provision of appropriate treatment to fix them. This Deep Learning-based solution identifies two classes of salient surface defects: stripped (worn-out slots) and surface damaged (dents, cracks, etc.) heads. This solution analyses the user-provided image data, identifies the best performing deep learning model architecture, and predicts the defect class with the highest probability score. This can assist fastener manufacturing companies in improving their quality control processes.
Highlights
- This solution identifies two types of surface defects in screw heads: stripping and surface damage. This solution can assist fastener manufacturing companies in improving their quality control processes.
- This solution analyses flat surface images of screw heads and identifies the best performing deep learning model architecture for defect classification. This solution improves the turnaround time for developing AI-powered visual inspection systems.
- Mphasis DeepInsights is a cloud-based cognitive computing platform that offers data extraction & predictive analytics capabilities. Need Customized Deep learning and Machine Learning Solutions? Get in Touch!
Details
Sold by
Categories
Delivery method
Latest version
Deployed on AWS
Unlock automation with AI agent solutions
Fast-track AI initiatives with agents, tools, and solutions from AWS Partners.
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.
Pricing
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.
Dimension | Description | Cost/host/hour |
|---|---|---|
ml.m5.2xlarge Inference (Batch) Recommended | Model inference on the ml.m5.2xlarge instance type, batch mode | $20.00 |
ml.m5.12xlarge Inference (Real-Time) Recommended | Model inference on the ml.m5.12xlarge instance type, real-time mode | $10.00 |
ml.m5.4xlarge Training Recommended | Algorithm training on the ml.m5.4xlarge instance type | $10.00 |
ml.m4.4xlarge Inference (Batch) | Model inference on the ml.m4.4xlarge instance type, batch mode | $20.00 |
ml.m5.4xlarge Inference (Batch) | Model inference on the ml.m5.4xlarge instance type, batch mode | $20.00 |
ml.m4.16xlarge Inference (Batch) | Model inference on the ml.m4.16xlarge instance type, batch mode | $20.00 |
ml.p3.16xlarge Inference (Batch) | Model inference on the ml.p3.16xlarge instance type, batch mode | $20.00 |
ml.m4.2xlarge Inference (Batch) | Model inference on the ml.m4.2xlarge instance type, batch mode | $20.00 |
ml.c5.2xlarge Inference (Batch) | Model inference on the ml.c5.2xlarge instance type, batch mode | $20.00 |
ml.p3.2xlarge Inference (Batch) | Model inference on the ml.p3.2xlarge instance type, batch mode | $20.00 |
Vendor refund policy
Currently we do not support refunds, but you can cancel your subscription to the service at any time.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA)Â .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
Amazon SageMaker algorithm
An Amazon SageMaker algorithm is a machine learning model that requires your training data to make predictions. Use the included training algorithm to generate your unique model artifact. Then deploy the 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:
Version release notes
This is the version 1.1 of the algorithm.
Additional details
Inputs
- Summary
This algorithm takes ZIP file as input. The ZIP file to be uploaded for testing must have images that are not classified.
- Input MIME type
- application/zip
https://github.com/Mphasis-ML-Marketplace/Screw-Heads-Surface-Defects-Classifier/tree/main/Sample%20Input
https://github.com/Mphasis-ML-Marketplace/Screw-Heads-Surface-Defects-Classifier/tree/main/Sample%20Input
Resources
Vendor resources
Support
Vendor support
For any assistance reach out to us at:
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.
Similar products
RUBICONSmartCity (TM) helps city governments run waste and recycling operations more efficiently and turns garbage trucks into mobile data collection centers.
RUBICONSmartCity (TM) helps city governments run waste and recycling operations more efficiently and turns garbage trucks into mobile data sensing assets.
RUBICONSmartCity (TM) helps city governments run waste and recycling operations more efficiently and turns garbage trucks into mobile data sensing assets.
RUBICONSmartCity (TM) helps city governments run waste and recycling operations more efficiently and turns garbage trucks into mobile data sensing assets.
Customer reviews
0 ratings
0 AWS reviews
|
1 external reviews
Star ratings include only reviews from verified AWS customers. External reviews can also include a star rating, but star ratings from external reviews are not averaged in with the AWS customer star ratings.
Pawan R.
Automated Image Classifier using DL make image classification much easier.
Reviewed on Oct 12, 2023
Review provided by G2
What do you like best about the product?
When evaluating the advantages of using deep learning for image classifiers, important points such as ease of use and cost-effectiveness need to be taken into account. Additionally, on the professional side, Auto DL helps improve data transparency and user understanding, which is especially important when separating images from large files for training and testing purposes.
What do you dislike about the product?
Automated deep learning image classifiers sometimes create problems in terms of transparency, information and needs, overfitting, intelligence, bias, interpretation, and judgment. It is important to consider these limitations as well as their benefits and specific use requirements.
What problems is the product solving and how is that benefiting you?
Automatic deep learning image classifiers solve many problems. It makes content easier to manage, improves truth seeking, improves diagnosis, improves business management and increases driving safety. These applications provide great benefits to our businesses, individuals and communities by increasing efficiency and accuracy in many areas.