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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.

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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. You simply need to supply images of objects or scenes you want to identify, and the service handles the rest.


With S3 Object Lambda you can add your own code to S3 GET requests to modify and process data as it is returned to an application. For the first time, you can use custom code to modify the data returned by standard S3 GET requests to filter rows, dynamically resize images, redact confidential data, and much more. Powered by AWS Lambda functions, your code runs on infrastructure that is fully managed by AWS, eliminating the need to create and store derivative copies of your data or to run expensive proxies, all with no changes required to applications.

With just a few clicks in the AWS Management Console, you can configure a Lambda function and attach it to a S3 Object Lambda Access Point. From that point forward, S3 will automatically call your Lambda function to process any data retrieved through the S3 Object Lambda Access Point, returning a transformed result back to the application. You can author and execute your own custom Lambda functions, tailoring S3 Object Lambda’s data transformation to your specific use case.

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Universal Time and Eastern Standard Time Converter Calculator, UTC and EST Conversion Table. Utc (zulu) pst/ aldt pdt/ mst mdt/ cst cdt/ est edt/ ast alst hst; 0000. 1600: 1700: 1800: 1900: 2000: 1500: 1400: 0100: 1700: 1800: 1900: 2000: 2100: 1600: 1500. Utc Universal Time Coordinated is 4 hours ahead of Eastern Daylight Time 2:00 am 02:00 in UTC is 10:00 pm 22:00 in EDT. UTC to EST call time Best time for a conference call or a meeting is between 1pm-6pm in UTC which corresponds to 8am-1pm in EST. 2:00 am 02:00 Universal Time Coordinated (UTC). Converting UTC to EST. This time zone converter lets you visually and very quickly convert UTC to EST and vice-versa. Simply mouse over the colored hour-tiles and glance at the hours selected by the column. UTC stands for Universal Time. EST is known as Eastern Standard Time. EST is 4 hours behind UTC. Coordinated Universal Time (UTC) is the primary time standard now, time zones around the world are expressed using offsets from UTC, UTC offset is the difference in hours and minutes from UTC, a time zone can be determined by adding or subtracting the number of UTC offset. Eastern Standard Time (EST) is UTC-5:00, and Eastern Daylight Time (EDT.