SceneXplain

Amazon Rekognition makes it easy to add image and video analysis to your applications using proven, highly scalable, deep learning technology that requires no machine learning expertise to use. With Amazon Rekognition, you can identify objects, people, text, scenes, and activities in images and videos, as well as detect any inappropriate content. Amazon Rekognition also provides highly accurate facial analysis and facial search capabilities that you can use to detect, analyze, and compare faces for a wide variety of user verification, people counting, and public safety use cases. With Amazon Rekognition Custom Labels, you can identify the objects and scenes in images that are specific to your business needs. For example, you can build a model to classify specific machine parts on your assembly line or to detect unhealthy plants. Amazon Rekognition Custom Labels takes care of the heavy lifting of model development for you, so no machine learning experience is required.

eXplain is a specialized code-analysis and legacy-system evaluation tool from PKS Software GmbH, designed to deeply analyze, map, document, and assess legacy applications, especially on mainframe platforms such as IBM i (AS/400) and IBM Z, so organizations can understand what lives in their software, how it’s structured, and what parts are worth keeping, refactoring or retiring. It imports existing source code into an independent “eXplain server”, no need to install anything on the host system, then uses advanced parsers to examine languages like COBOL, PL/I, Assembler, Natural, RPG, JCL, and others, along with data about databases (Db2, Adabas, IMS), job-schedulers, transaction monitors, and more. eXplain builds a central repository that becomes a knowledge hub; from there, it generates cross-language dependency graphs, data-flow maps, interface analyses, clusterings of related modules, and detailed object-and-resource usage reports.