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Classification-Image (166 results) showing 81 - 90



This solution will evaluate between several deep learning models of various architectures on the user provided data. It will identify the best performing deep learning model architecture on the basis of validation metric for image classification. This will reduce the time and effort for the...

Algorithm - Fulfilled on Amazon SageMaker


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...

Algorithm - Fulfilled on Amazon SageMaker


In poisoning attack, attacker designed noises- such as image objects, variables value changes, label changes- are induced to the training data to test fidelity and robustness of model training. The model trained on such adverse dataset could systematically result in model vulnerability issues. For...

Algorithm - Fulfilled on Amazon SageMaker

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The Hard Hat Detector for Industrial Worker Safety - is a computer vision-driven ML model designed to detect PPE compliance/non-compliance on the factory floor or at the construction site in real time. It analyzes image footage, identifies workers, and checks if they follow safety regulations,...

Model Package - Fulfilled on Amazon SageMaker


This is a hybrid classical-quantum machine learning based solution which detects Pneumothorax from chest x-ray images. This solution adopts Quanvolutional Neural Network (QNN) to extract useful features in the data for classification purposes. A variational circuit with an optimizable parameter...

Model Package - Fulfilled on Amazon SageMaker


This is an Image Classification model from [TensorFlow Hub](https://tfhub.dev/google/imagenet/mobilenet_v2_035_224/classification/4). It takes an image as input and classifies the image to one of the multiple classes. The model available for deployment is pre-trained on ImageNet which comprises...

Model Package - Fulfilled on Amazon SageMaker


This is an Image Classification model from [PyTorch Hub](https://pytorch.org/hub/pytorch_vision_wide_resnet/). It takes an image as input and classifies the image to one of the multiple classes. The model available for deployment is pre-trained on ImageNet which comprises images of different...

Model Package - Fulfilled on Amazon SageMaker


Surface defects in sheet steel poses quality and performance risks. Classifying various defects allows to quickly identify and remove the causes of their occurrence. This Transfer Learning-based solution identifies three classes of surface defects: holes, peels, and others (cracks, scratches,...

Model Package - Fulfilled on Amazon SageMaker


This is an Image Classification model from [PyTorch Hub](https://pytorch.org/hub/pytorch_vision_densenet/). It takes an image as input and classifies the image to one of the multiple classes. The model available for deployment is pre-trained on ImageNet which comprises images of different classes....

Model Package - Fulfilled on Amazon SageMaker


Usually, significant amount of time spent by the farmers to check the health status of plants and fruits. Inspection procedure can be automated with the help machine learning model that processes crop images and classifies as good or defective. This model is trained on images of tomatoes and plants...

Model Package - Fulfilled on Amazon SageMaker