# Facial recognition Published articles for Facial recognition. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Frequently Asked Questions about FHE DevFeed: [Frequently Asked Questions about FHE]() Original publisher: [Read original article]() Published: 2025-07-18T17:31:49Z Content type: article Language: en Sources: [Jeremy Kun]() Topics: [homomorphic encryption](), [FHE](), [Cryptography](), [math](), [GPU](), [Facial recognition](), [Sorting]() Tags: [cryptography](), [encryption](), [facial-recognition](), [fhe](), [gpu](), [homomorphic-encryption](), [mathematics](), [programming]() ### AI overview A collection of short answers about fully homomorphic encryption (FHE), covering encrypted queries, computation on ciphertexts, sorting, performance, and security against quantum computers. The article explains that FHE can support operations on encrypted data without exposing the underlying plaintext, while computational overhead remains a key limitation. ### Source excerpt I work on homomorphic encryption (HE or FHE for "fully" homomorphic encryption) and I have written a lot about it on this blog (see the relevant tag). This article is a collection of short answers to questions I see on various threads and news aggregators discussing FHE. Facts If a service uses FHE and can respond to encrypted queries, can't the service see your query? How is it possible to operate on encrypted data without seeing it? ## ESP-SparkBot：Large Language Model Robot with ESP32-S3 DevFeed: [ESP-SparkBot：Large Language Model Robot with ESP32-S3]() Original publisher: [Read original article]() Author: John Lee Published: 2025-04-23T00:00:00Z Content type: article Language: en Sources: [Blog on Developer Portal]() Topics: [ESP32-S3](), [Hardware](), [Artificial Intelligence](), [Language models](), [Development]() Tags: [artificial-intelligence](), [blog](), [debugging](), [esp-now](), [esp32-s3](), [face-recognition](), [facial-recognition](), [hardware](), [home-automation](), [language-models](), [motion-detection](), [offline-speech-recognition](), [usb-screen-mirror](), [video]() ### AI overview This article introduces ESP-SparkBot, a low-cost, multifunctional AI robot built with ESP32-S3. It describes the robot's voice interaction, facial recognition, remote control, motion detection, multimedia capabilities, hardware design, power options, and supporting software framework. ### Source excerpt This article provides an overview of the ESP-SparkBot, its features, and functionality.It also details the hardware design and outlines the software framework that supports its operation. Introduction# With the booming development of generative artificial intelligence, large language models (LLMs) are becoming a core technology in the AI field. ## Launch Week 5 Hackathon Winners DevFeed: [Launch Week 5 Hackathon Winners]() Original publisher: [Read original article]() Author: Tyler Shukert Published: 2022-08-25T07:00:00Z Content type: news Language: en Sources: [Supabase Blog]() Topics: [Supabase](), [Hackathon](), [Caching](), [React](), [ui](), [Security](), [Facial recognition](), [stripe](), [Flutter](), [App]() Tags: [caching](), [facial-recognition](), [flutter](), [open-source](), [react](), [security](), [stripe](), [ui]() ### AI overview Supabase announces the winners of its Launch Week 5 Hackathon, which received 46 submissions. The winning projects include a Supabase caching utility library, a React UI component library, a job board app, a notes and links app, a security desktop app, a Stripe data synchronization tool, a facial-recognition game, a quiz app, and a video journaling app. ### Source excerpt Announcing the winners of the Launch Week 5 Hackathon! ## Encryption & Privacy Policy and Technology DevFeed: [Encryption & Privacy Policy and Technology]() Original publisher: [Read original article]() Author: Adam Published: 2019-12-11T00:00:00Z Content type: opinion Language: en Sources: [Shostack & Friends Blog]() Topics: [Encryption](), [Facial recognition](), [Cryptography](), [recommendations]() Tags: [encryption](), [facial-recognition](), [privacy](), [recommendations](), [research]() ### AI overview A commentary roundup discusses an open letter arguing that weak encryption puts internet users at risk, nominations for the Caspar Bowden Award for privacy-enhancing technology research, and proposed rules for facial recognition technology at the Port of Seattle. ### Source excerpt A few tidbits in recent news. ## Eigenfaces, for Facial Recognition DevFeed: [Eigenfaces, for Facial Recognition]() Original publisher: [Read original article]() Published: 2011-07-27T18:41:01Z Content type: tutorial Language: en Sources: [Jeremy Kun]() Topics: [Facial recognition](), [Algorithm]() Tags: [algorithm](), [covariance](), [eigenfaces](), [facial-recognition](), [images](), [inner-product](), [linear-algebra](), [mathematics](), [pixel](), [programming](), [vector]() ### AI overview This tutorial introduces eigenfaces for facial recognition. It outlines collecting sample face images, training a recognition algorithm, and classifying new images, then explains how grayscale images can be represented as matrices and vectors in a high-dimensional face space. ### Source excerpt This post assumes familiarity with the terminology and notation of linear algebra, particularly inner product spaces. Fortunately, we have both a beginner's primer on linear algebra and a follow-up primer on inner products. The Quest We are on a quest to write a program which recognizes images of faces. The general algorithm should be as follows. Get a bunch of sample images of people we want to recognize. Train our recognition algorithm on those samples.