To specify the language model name, write language shortcut after -l flag, by default, it takes the English language:. However, there can be many complications here. Sometimes, the OCR might not perform well due to the ambiguity of the data we are using.
For example, the text might be placed across different images, which might misplace the extracted text; similarly, OCR might not perform well when there is any handwritten text. This is where Deep Learning algorithms come into the picture.
To make PDFs searchable using deep learning techniques, one must first understand different ways of information extraction. Today, deep learning, neural networks in specific have achieved a state of the art performance in extracting any kind of text-based data. These algorithms are trained on a wide range of datasets over different parameters.
The process begins with an application that converts the PDF into a series of images. The images are then split into individual pages.
Each page is assigned a category based on the contents in the page. The categories are used to train the neural network to extract relevant information from the document.
The network is trained for accuracy through a process called backpropagation. The backpropagation algorithm is used to calculate the error rate of the network. The error rate determines how many times the network should adjust its weights to extract the best information.
This error rate is again optimised by setting and updating the hyper-parameters of the network. However, today we need not do everything from scratch, we can utilise pre-trained models such as RESNET, BERT which are already trained on a wide range of data and build a simple neural network on top of it.
After the model is trained and evaluated we then create a new electronic PDF or can save them in specific formats as required by the user. Following are some of the state-of-the-art research work that can be used for data extraction from PDF to create searchable PDFs. With this, any information, say PDF, Images, can be instantly extracted and can be made searchable.
This can significantly help enterprises manage their operations more effectively and increase work, revenue efficiency, and productivity without writing a single line of code. In the next section, we will discuss in detail how we can convert unstructured PDF files into readable and searchable files using the Nanonets. Nanonets recently announced a set of new search features with the best OCR technology, with this, users can find documents not only by searching for keywords but also by opening a PDF file and searching for a phrase or a word inside the document.
This feature will help users to find the right content quickly and easily. There are no limitations here, the search will work on any kind of PDF data or even images. Nanonets platform automatically parses through all the files using its advanced OCR and returns the files that contain the value. For example, say we have an invoice extraction model and search for text in an invoice, say a key. You can leverage the search option on the top right corner and directly enter the text.
This will return all the files that contain this text, just like any other Adobe acrobat but with more precision. For example, say you have to filter PDFs based on the invoice date and invoice total.
Now, under your model settings, you can set the formatting type to a particular data type for your model, in this case, the date is set to the date-time format and the invoice is set to the integer as seen in the screenshot below. The expected behaviour is to return all PDFs that contain the match date and invoice total. But, Nanonets intelligently identifies the date and invoice based on content and the position of the invoice and returns only the sorted invoices that match the given search input.
Connie has been writing for Mac productivity and utility apps since Each review and solution is based on her practical tests, she is aways energetic and trustworthy in this field. Free Download Buy Now. Connie Wisley December 06, 3. Connie Wisley. Comments 0 Leave a Reply. You can configure any folder in your system as a magic folder. It makes the image or scanned pdf searchable. The advantage of the searchable pdf is that you can copy text or search for text just like any other document.
The biggest advantage of them all is the scanned document content now starts appearing in your file search results. Forget about manually detecting text in your scanned document and manually converting image-based documents to searchable PDFs.
Work towards your goal of a paperless office. With our smart OCR technology, you can incorporate scanned documents with search capability into your smart digital workplace. Toggle navigation.
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