Merge pull request #190045 from PatrickFarley/freshness-pass

[cog svcs] Freshness pass

Author: jborsecnik

articles/cognitive-services/Computer-vision/concept-brand-detection.md

@@ -1,7 +1,7 @@
 ---
 title: Brand detection - Computer Vision
 titleSuffix: Azure Cognitive Services
-description: This article discusses a specialized mode of object detection; brand and/or logo detection using the Computer Vision API.
+description: Learn about brand and logo detection, a specialized mode of object detection, using the Computer Vision API.
 services: cognitive-services
 author: PatrickFarley
 manager: nitinme

articles/cognitive-services/Computer-vision/index.yml

@@ -12,7 +12,7 @@ metadata:
   ms.topic: hub-page # Required
   author: PatrickFarley #Required; your GitHub user alias, with correct capitalization.
   ms.author: pafarley #Required; microsoft alias of author; optional team alias.
-  ms.date: 03/31/2021 #Required; mm/dd/yyyy format.
+  ms.date: 02/28/2022 #Required; mm/dd/yyyy format.
 
 highlightedContent:
   # itemType: architecture | concept | deploy | download | get-started | how-to-guide | learn | overview | quickstart | reference | tutorial | whats-new

articles/cognitive-services/Computer-vision/overview.md

@@ -9,7 +9,7 @@ manager: nitinme
 ms.service: cognitive-services 
 ms.subservice: computer-vision 
 ms.topic: overview
-ms.date: 09/28/2021
+ms.date: 02/28/2022
 ms.author: pafarley
 ms.custom: [seodec18, cog-serv-seo-aug-2020, contperf-fy21q2]
 keywords: computer vision, computer vision applications, computer vision service

articles/cognitive-services/Custom-Vision-Service/overview.md

@@ -9,7 +9,7 @@ manager: nitinme
 ms.service: cognitive-services
 ms.subservice: custom-vision
 ms.topic: overview
-ms.date: 08/25/2021
+ms.date: 02/28/2022
 ms.author: pafarley
 ms.custom: cog-serv-seo-aug-2020
 keywords: image recognition, image identifier, image recognition app, custom vision
@@ -18,7 +18,7 @@ keywords: image recognition, image identifier, image recognition app, custom vis
 
 # What is Custom Vision?
 
-Azure Custom Vision is an image recognition service that lets you build, deploy, and improve your own image identifier models. An image identifier applies labels (which represent classifications or objects) to images, according to their detected visual characteristics. Unlike the [Computer Vision](../computer-vision/overview.md) service, Custom Vision allows you to specify your own labels and train custom models to detect them.
+Azure Custom Vision is an image recognition service that lets you build, deploy, and improve your own image identifier models. An image identifier applies labels to images, according to their detected visual characteristics. Each label represents a classifications or objects. Unlike the [Computer Vision](../computer-vision/overview.md) service, Custom Vision allows you to specify your own labels and train custom models to detect them.
 
 This documentation contains the following types of articles:
 * The [quickstarts](./getting-started-build-a-classifier.md) are step-by-step instructions that let you make calls to the service and get results in a short period of time.
@@ -28,11 +28,11 @@ This documentation contains the following types of articles:
 
 ## What it does
 
-The Custom Vision service uses a machine learning algorithm to analyze images. You, the developer, submit groups of images that feature and lack the characteristics in question. You label the images yourself at the time of submission. Then, the algorithm trains to this data and calculates its own accuracy by testing itself on those same images. Once you've trained the algorithm, you can test, retrain, and eventually use it in your image recognition app to [classify images](getting-started-build-a-classifier.md). You can also [export the model](export-your-model.md) itself for offline use.
+The Custom Vision service uses a machine learning algorithm to analyze images. You, the developer, submit groups of images that have and don't have the characteristics in question. You label the images yourself at the time of submission. Then the algorithm trains to this data and calculates its own accuracy by testing itself on those same images. Once you've trained the algorithm, you can test, retrain, and eventually use it in your image recognition app to [classify images](getting-started-build-a-classifier.md). You can also [export the model](export-your-model.md) itself for offline use.
 
 ### Classification and object detection
 
-Custom Vision functionality can be divided into two features. **[Image classification](getting-started-build-a-classifier.md)** applies one or more labels to an image. **[Object detection](get-started-build-detector.md)** is similar, but it also returns the coordinates in the image where the applied label(s) can be found.
+Custom Vision functionality can be divided into two features. **[Image classification](getting-started-build-a-classifier.md)** applies one or more labels to an entire image. **[Object detection](get-started-build-detector.md)** is similar, but it returns the coordinates in the image where the applied label(s) can be found.
 
 ### Optimization
 
@@ -42,11 +42,11 @@ Additionally, you can choose from several variations of the Custom Vision algori
 
 ## What it includes
 
-The Custom Vision Service is available as a set of native SDKs as well as through a web-based interface on the [Custom Vision website](https://customvision.ai/). You can create, test, and train a model through either interface or use both together.
+The Custom Vision Service is available as a set of native SDKs as well as through a web-based interface on the [Custom Vision portal](https://customvision.ai/). You can create, test, and train a model through either interface or use both together.
 
 ### Supported browsers for Custom Vision web portal
 
-The Custom Vision web interface can be used by the following web browsers:
+The Custom Vision portal can be used by the following web browsers:
 -	Microsoft Edge (latest version)
 -	Google Chrome (latest version)
 
@@ -58,4 +58,4 @@ As with all of the Cognitive Services, developers using the Custom Vision servic
 
 ## Next steps
 
-Follow the [Build a classifier](getting-started-build-a-classifier.md) guide to get started using Custom Vision on the web portal, or complete a [quickstart](quickstarts/image-classification.md) to implement the basic scenarios in code.
+Follow the [Build a classifier](getting-started-build-a-classifier.md) quickstart to get started using Custom Vision on the web portal, or complete an [SDK quickstart](quickstarts/image-classification.md) to implement the basic scenarios in code.

articles/cognitive-services/Face/Overview.md

@@ -8,7 +8,7 @@ manager: nitinme
 ms.service: cognitive-services
 ms.subservice: face-api
 ms.topic: overview
-ms.date: 09/27/2021
+ms.date: 02/28/2022
 ms.author: pafarley
 ms.custom: cog-serv-seo-aug-2020
 keywords: facial recognition, facial recognition software, facial analysis, face matching, face recognition app, face search by image, facial recognition search
@@ -30,11 +30,11 @@ This documentation contains the following types of articles:
 
 ## Example use cases
 
-Identity verification: Verify someone's identity against a government-issued ID card like a passport or driver's license or other enrollment image. You can use this verification to grant access to digital or physical services or recover an account. Specific access scenarios include opening a new account, verifying a worker, or administering an online assessment. Identity verification can be done once when a person is onboarded, and repeated when they access a digital or physical service.
+**Identity verification**: Verify someone's identity against a government-issued ID card like a passport or driver's license or other enrollment image. You can use this verification to grant access to digital or physical services or recover an account. Specific access scenarios include opening a new account, verifying a worker, or administering an online assessment. Identity verification can be done once when a person is onboarded, and repeated when they access a digital or physical service.
 
-Touchless access control: Compared to today’s methods like cards or tickets, opt-in face identification enables an enhanced access control experience while reducing the hygiene and security risks from card sharing, loss, or theft. Facial recognition assists the check-in process with a human in the loop for check-ins in airports, stadiums, theme parks, buildings, reception kiosks at offices, hospitals, gyms, clubs, or schools.
+**Touchless access control**: Compared to today’s methods like cards or tickets, opt-in face identification enables an enhanced access control experience while reducing the hygiene and security risks from card sharing, loss, or theft. Facial recognition assists the check-in process with a human in the loop for check-ins in airports, stadiums, theme parks, buildings, reception kiosks at offices, hospitals, gyms, clubs, or schools.
 
-Face redaction: Redact or blur detected faces of people recorded in a video to protect their privacy.
+**Face redaction**: Redact or blur detected faces of people recorded in a video to protect their privacy.
 
 
 ## Face detection and analysis
@@ -94,12 +94,6 @@ The Group operation divides a set of unknown faces into several smaller groups b
 
 All of the faces in a returned group are likely to belong to the same person, but there can be several different groups for a single person. Those groups are differentiated by another factor, such as expression, for example. For more information, see the [Facial recognition](concepts/face-recognition.md) concepts guide or the [Group API](https://westus.dev.cognitive.microsoft.com/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395238) reference documentation.
 
-## Sample apps
-
-The following sample applications show a few ways to use the Face service:
-
-- [FamilyNotes UWP app](https://github.com/Microsoft/Windows-appsample-familynotes) is a Universal Windows Platform (UWP) app that uses face identification along with speech, Cortana, ink, and camera in a family note-sharing scenario.
-
 ## Data privacy and security
 
 As with all of the Cognitive Services resources, developers who use the Face service must be aware of Microsoft's policies on customer data. For more information, see the [Cognitive Services page](https://www.microsoft.com/trustcenter/cloudservices/cognitiveservices) on the Microsoft Trust Center.