Time for an update on my ongoing person identification in images project; for all the background you can check out these previous posts: Analyzing AWS Rekognition Accuracy with Neo4j AWS Rekognition Graph Analysis – Person Label Accuracy Person Recognition: OpenCV vs. AWS Rekognition In my earlier serverless series I discussed and provided code for getting… Continue reading Person Recognition in Images with OpenCV & Neo4j
Tag: graph
AWS Rekognition Graph Analysis – Person Label Accuracy
Last week I wrote a post evaluating AWS Rekognition accuracy in finding people in images. The analysis was performed using the Neo4j graph database. As I noted in the original post – Rekognition is either very confident it has identified a person or not confident at all. This leads to an enormous number of false… Continue reading AWS Rekognition Graph Analysis – Person Label Accuracy
Analyzing AWS Rekognition Accuracy with Neo4j
As an extension of my series of posts on handling IoT security camera images with a Serverless architecture I’ve extended the capability to integrate AWS Rekognition Amazon Rekognition is a service that makes it easy to add image analysis to your applications. With Rekognition, you can detect objects, scenes, and faces in images. You can… Continue reading Analyzing AWS Rekognition Accuracy with Neo4j
Upping your data game with Graph Databases
Since the late-2000’s there has been an explosion of non-relational (NoSQL if you must) data persistence technology. The industry buzz has focused around the derivatives of the seminal work done at Google – i.e., BigTable – and Amazon – i.e., Dynamo. We’ve seen massive adoption of simple document stores and key-value based stores – which… Continue reading Upping your data game with Graph Databases