This solution takes a set of images as input and produces a 3D model of the scene as output. It first performs Structure-from-Motion (SfM) to estimate the camera poses and sparse 3D points from the images. It then performs Multi-View Stereo (MVS) to refine the 3D points and generate a dense point...
Algorithm - Fulfilled on Amazon SageMaker
This is an object detection model from [TensorFlow Hub](https://tfhub.dev/tensorflow/faster_rcnn/resnet152_v1_800x1333/1). It takes an image as input and returns bounding boxes for the objects in the image. The model is pre-trained on COCO 2017 which comprises images with multiple objects and the...
Model Package - Fulfilled on Amazon SageMaker
This is a Sentence Pair Classification model built upon a Text Embedding model from [PyTorch Hub](https://pytorch.org/hub/huggingface_pytorch-transformers/). It takes a pair of sentences as input and classifies the input pair to 'entailment' or 'no-entailment'. The class label entailment implies...
Model Package - Fulfilled on Amazon SageMaker
This solution takes a deep learning-based approach to learn and understand the patterns in Temperature sensor data. It aims at learning the normal behavior patterns of the sensor data during training process using generative algorithms. Once trained, the model can monitor and identify abnormal...
Algorithm - Fulfilled on Amazon SageMaker
Generate simulations of interest rate predictions using market information. Since mortgage terms can be 30 years, this model has a 30-year prediction. The model using the Monte Carlo simulation, a simulation model that shows some fluctuation among three scenarios to generate a record path. If you...
Model Package - Fulfilled on Amazon SageMaker
Sentiment classification is one of the most common problems prevelant in the industry. Getting labelled data in less time to train a classifier is a tedious task. This solution takes input of unlabeled text data and generates initial/base labels using BERT based pre-trained model for sentiment...
Algorithm - Fulfilled on Amazon SageMaker
Mphasis server storage forecasting helps businesses assess the storage space on their servers based on historic data. This will help businesses get an understanding of their server usage and help them plan better. It uses ensemble ML algorithms with automatic model selection algorithms. This...
Model Package - Fulfilled on Amazon SageMaker
This is an Image Classification model from [TensorFlow Hub](https://tfhub.dev/google/bit/m-r50x1/imagenet21k_classification/1). 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-21k which comprises...
Model Package - Fulfilled on Amazon SageMaker
Use NeoPulse® to build models for most types of machine learning problems including, but not limited to, sentiment analysis, object detection, object recognition, classification and regression. Novices and experts can easily create AI models, using custom data, with as little as 14 lines of code in...
Algorithm - Fulfilled on Amazon SageMaker
This is an Image Classification model from [TensorFlow Hub](https://tfhub.dev/google/efficientnet/b6/classification/1). 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...
Model Package - Fulfilled on Amazon SageMaker
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