Search: add-log-fields

to capture. In this article, we will show how to add field for model There are 2 types of fields: Form Field and Table Field 1. Add Form Field Step 1: On Add Learning Instance screen, click "Add Field" button

Step 4: Click "Save" button 2. Add Table and Table fields Step 1: On Add Learning Instance screen

[2] Add New Field for Model

Add New Field for Model

needs to define field to capture. In this article, we will show how to add field for model There are 2 types of fields: Form Field and Table Field == **1. Add Form Field** == (% class="box infomessage" %) ((( **Step 1: **On Add Learning Instance screen, click "Add Field" button on the line of "Form Field

choose base model, this new model will get all the fields that the based model has and staff can add more fields by clicking button "Add field" or remove fields by unticking some fields. If staff doesn't

" button Note: Staff can not add, remove and configure fields after saving. So please check carefully

, this new model will get all the fields that the based model has and staff can add more fields by clicking button "Add field" or remove fields by unticking some fields. [[image:image-20230213141833-4.png

"]] (% class="box infomessage" %) ((( **Step 2**: Choose "Add Learning Model" button ))) [[image:image

Step 3: Modify tags and click "Apply" button There are 4 options to modify tags: Add to existing: Add to existing is used for adding more tags for chose documents. A staff can choose option "Add to existing" then choose other tags or add new tags then click "Apply" button Clear fields: Clear fields

))) There are 4 options to modify tags: * **Add to existing**: Add to existing is used for adding more tags for chose documents. A staff can choose option "Add to existing" then choose other tags or add new tags then click "Apply" button [[image:image-20221027174657-4.png||cursorshover="true"]] * **Clear fields

. Adding a new table In order to create a new table, click [Add Field], select Data Type = “table

A basic element in the extraction schema is the data field. However, akaBot Vision enables the capture of even more complex structures like tables. Adding a predefined table field If you are missing

, click [Add Field], select Data Type = “table” and then input the value you want to create a new table

="wikigeneratedid" id="HParagraph1" %) A basic element in the extraction schema is the data field. However, akaBot

field** == If you are missing some fields when capturing data from the document, navigate to the Fields

this stage, user can make changes to the text in each field that has been detected incorrectly In addition, akaBot Vision provides users with the capability to add or remove rows in a table To insert a row, you can click "+" icon To delete a row, you can click "x" icon To add a new row at the end of the table

in each field that has been detected incorrectly [[image:image-20220420193327-2.png||data-xwiki-image-style-alignment="center"]] In addition, akaBot Vision provides users with the capability to add

" icon * To add a new row at the end of the table, you can click on the "Add row" button These features

Create New Learning Model Add New Field for Model Exclude Documents When Training Model Modify Tags for Documents

* [[Create New Learning Model>>https://docs.akabot.com/bin/view/akaBot%20Vision/Learning%20Models/Create%20New%20Model/]] * [[Add New Field for Model>>https://docs.akabot.com/bin/view/akaBot%20Vision/Learning%20Models/Add%20New%20Field%20for%20Model/]] * [[Exclude Documents When Training Model>>https

Each Pipeline defines the structure of Data fields that akaBot Vision extracts. Description When editing this structure you have two options: Use pre-trained Data fields – AkaBot Vision’s Generic AI engine has been pre-trained to recognize specific Data fields and enables you to start extracting data

[3] Configure Fields for Data Extraction

Configuring Fields for Data Extraction

="wikigeneratedid" id="HParagraph1" %) Each Pipeline defines the structure of Data fields that akaBot Vision

options: * Use pre-trained Data fields – AkaBot Vision’s Generic AI engine has been pre-trained to recognize specific Data fields and enables you to start extracting data without any additional training

on the top menu bar, then click Users on the left side menu. Step 2: Click on the Add user button in the upper right corner. A pop-up will be shown. Then enter the account's information in all the fields

"]] **Step 2**: Click on the **Add user** button in the upper right corner. A pop-up will be shown. Then enter the account's information in all the fields [[image:image-20220420094636-4.png]] **Step 3

1. Create an Account Note: Although akaBot Vision currently supports Pre-trained data fields

by filling in all the fields or register with your current Google count by clicking "Sign up with Google

customizable, so you can add/group/remove pipelines as needed. Table of Content

currently supports Pre-trained data fields only for Invoice processing, the technology is documented

]] (% class="box infomessage" %) ((( Note: You can register by filling in all the fields or register with your

document type that needs to be processed. The left panel is fully customizable, so you can add/group/remove

in akaBot Vision work? a. Import Document The user has to log in to akaBot Vision to get token

createDate string Date upload document dataMappings array dataMerge string Mapping results between field

has to log in to akaBot Vision to get token in the API Key in the Account section below the user's

document |dataMappings|array| |dataMerge|string|Mapping results between field to capture and AI’s results