You could try an online service like https://extract-io.web.app/ or https://docparser.com/. Source: almost 2 years ago

DocParser: DocParser simplifies the extraction of structured data from various file formats, such as PDFs and scanned documents, directly into Google Sheets. By automating this process, DocParser saves valuable time and effort otherwise spent on manual data entry. Link to DocParser. Source: about 2 years ago

There are several tools available today that can help you extract tables from PDF files (such as Tabula), or even parse PDFs into structured JSON using AI (like Parsio -> I'm the founder) or without AI (like Docparser). Source: about 2 years ago

Thank you for sharing those! I didn't know them I've only checked this one https://docparser.com/ and I think my solution could be better because it will be easier for the user. Source: about 2 years ago

As previously suggested, if the layout of your PDFs never changes (consistent column widths in tables and placement), you can use a zonal PDF parser like DocParser. Alternatively, an AI-powered parser may be a better choice. Source: over 2 years ago

One effective way to balance the benefits of face analysis with privacy concerns is through anonymization techniques. By anonymizing data, organizers can protect attendee privacy while still leveraging face analysis for access control and security. For example, API4AI’s Image Anonymization API can blur or mask facial features, allowing facial recognition without exposing individual identities. - Source: dev.to / 7 months ago

Image anonymization is an effective solution that allows retailers to shield individual identities captured on surveillance footage. By employing AI to blur faces or remove personally identifiable information (PII) from video streams, security teams can monitor store activities without violating customer privacy. These methods ensure that sensitive data isn’t retained or misused, lowering the risk of privacy... - Source: dev.to / 7 months ago

Anonymization: One of the most effective strategies for protecting privacy in AI-driven moderation is anonymization. This process ensures that sensitive data, such as faces or other identifiable features, are obscured or blurred during analysis. For instance, image anonymization technologies can obscure faces or sensitive areas in an image before it is processed by an AI model. This allows the system to... - Source: dev.to / 7 months ago

One major privacy concern in online education is the frequent use of video conferencing and image sharing, which can put student identities at risk. Image Anonymization APIs offer a solution by automatically detecting and blurring faces in photos or videos, ensuring that students' identities remain protected during remote learning sessions. Whether it’s a classroom recording, a group project, or a live video... - Source: dev.to / 8 months ago

On a busy construction site, real-time monitoring of worker activities, safety protocols, and compliance is crucial. However, this must be done in a way that respects workers' privacy. Image anonymization technologies allow companies to mask or blur faces in images and video feeds, ensuring that personal identities remain confidential. This approach enables the collection of vital site data, such as worker... - Source: dev.to / 8 months ago