• Skip to main content
  • Skip to secondary menu
  • Skip to footer

Technologies.org

Technology Trends: Follow the Money

  • Technology Events 2026-2027
  • Sponsored Post
  • Technology Markets
  • About
    • GDPR
  • Contact

Panasonic Launches API for Facial Recognition Powered by Deep Learning Technology

November 25, 2019 By admin

Panasonic first began R&D into facial recognition in the early 1990s, and has continued to perfect these capabilities in various ways by incorporating the technology into consumer products and by applying it to camera-based security solutions. The company has gone on to provide reliable, safe and efficient facial recognition solutions such as for passport control at airports and ticketless entry at amusement parks. Now, Panasonic aims to help customers solve a variety of challenges by offering an API for this same technology. Panasonic Corporation announced that starting November 25, 2019, the company will begin offering an application programming interface (API) for its facial recognition technology to the market in Japan. The API enables deep-learning powered facial recognition technology via a cloud-based service.

By adding an API to its facial recognition service lineup, Panasonic has the advantage of being able to offer both on-premises and cloud-based solutions to match its customers’ business requirements. Making Panasonic’s proven facial recognition technology available to customers and partners through an API will enable it to be used in a wider range of industries, including for marketing analysis, accounting, and entry/exit management. This will enable further quality improvements and the creation of new collaborative business models with its customers and partners through open innovation. Through this, Panasonic will strive to further accelerate growth and expand its customer base.

Advancements in ICT and other technologies mean that identity verification and entry/exit management are becoming more efficient. Meanwhile, there are a range of issues related to these that require solutions such as individuals working in logistics fields needing to be able to pass security points even with both hands full, and that employees often work from varying offices all requiring unified access and timecard management. There are also other more serious problems, such as online identity theft.

Strengths of Panasonic’s facial recognition technology:

  • Feature quantity generation method of recognizing the whole face and certain parts of the face through the integration of multiple deep learning technologies.
  • Proprietary Panasonic algorithm that performs a degree of similarity calculation method for matching faces and controlling errors caused by photographic conditions.

Due to these features, Panasonic’s facial recognition technology is able to accurately identify faces even under difficult conditions which previously presented challenges to facial recognition, such as when the face is seen from an angle, in difficult lighting conditions, or when the face is partially covered by sunglasses or a surgical mask.

Main Features of the Facial Recognition API
1. Provides world-class advanced facial recognition technology as a cloud service
Panasonic’s world-class facial recognition technology is capable of recognizing faces even when seen from an angle, faces that have aged from the registered photo, and faces that are partially covered. The technology also makes use of the backlight correction and noise reduction technology the company has developed as a camera manufacturer.

2. Usage-based pricing model, with no initial costs
Panasonic’s deep learning-based facial recognition technology can now be used simply by opening this API, making it possible to incorporate the technology into customers’ smartphone applications, websites, and building access management systems. This will enable entry/exit management at multiple business sites, streamline movement within offices or work sites, and prevent identity theft. The facial recognition API is a micro service within Panasonic’s μSockets B2B IoT service which is currently available in Japan.

Source: Panasonic

Filed Under: Tech Tagged With: Deep Learning Technology, Facial Recognition, Panasonic, api

Footer

Recent Posts

  • inDrive and Pony.ai Target Kazakhstan for a Robotaxi Project Built on NVIDIA Technology
  • Applied Ventures Backs Albert Invent as Materials Research Becomes an AI Battleground
  • Pathos AI Raises $237 Million as BMS and Tempus Back a Broader Drug Development Push
  • Tractian Raises $130 Million Series D at $1.4 Billion Valuation for AI That Predicts Machine Failures
  • Jensen Huang Has a Strong Case Against the 2029 Memory Glut Theory
  • Dream Labs Raises $90 Million to Build Brains for Everyday Robots
  • Venture Capital Digest, October 19, 2026: Tenstorrent Leads a Day of Major Technology Funding
  • Technology Digest, October 19, 2026: Nvidia’s CPU Push, AI Infrastructure Costs and the Next Chip Race
  • Texas Instruments Targets the Tiny Power Faults That Can Disrupt AI Data Centers
  • d-Matrix Begins Shipping Large AI Inference Clusters as Specialized Compute Gains Ground

Media Partners

  • Market Analysis
  • BareProxy.com
  • App Coding
Stocks Fall as Meta Capex Outruns Its Cash Flow, Chips Sink and Brent Tops $111
Why China’s Alleged Memory Chip Breakthrough Should Be Taken With a Grain of Salt
EnergyX’s Trafigura Deal Moves Lithium Extraction From Technology Promise Toward Commercial Scale
Marvell’s New Memory Expanders Target the Economics of AI Inference
AI Financing Fears Are Overrated: Hyperscaler Debt and Nvidia’s Vendor Deals Sit on Real Revenue
HyperCrux Market Analysis: Agent Memory and Local AI Drive Demand for a One-File Multi-Model Database
Small Infrastructure Primitives Run the $700 Billion AI Buildout, and Open Source Is How They Get Adopted
Screening Startup and Product Ideas After a Brainstorm: Four Questions, Money First
An AI Lab Is Paying Up Front for Atlas Energy’s (AESI) Generators as Agentic AI Multiplies Token Demand
Oracle’s Force Majeure Notice on Project Jupiter Shows Where AI Data Center Risk Is Landing
BareProxy Adds AI Crawler Control That Tells Real GPTBot and ClaudeBot Requests From Fakes
BareProxy Adds Bot Challenges That Make Scrapers Posing as Browsers Solve a Puzzle First
BareProxy Adds Cookie Consent That Holds Back Tracking Cookies Until a Visitor Says Yes
BareProxy Adds Markdown Serving That Turns Markdown Files Into Web Pages With No Build Step
BareProxy Ships Its First Nine Plugins, From Maintenance Pages and CORS to Geo Rules and Rate Limits
BareProxy 0.2.0 Runs WebAssembly Plugins Through the Proxy-Wasm Interface
BareProxy 0.3.0 Writes Its Plugins in Rust, Where a Plugin Adds 15 Microseconds Instead of 42
BareProxy Is an Operating System for Web Traffic: A Small Core and a Long Stream of Plugins
BareProxy Plugins Go WebAssembly, Starting With RenderCache and AI Crawler Control
BareProxy Runs on Linux, macOS and Windows, and One Plugin File Runs on All of Them
Apple's US Link-Out Fee Is Zero Until a Judge Sets It, and Apple Is Asking for Up to 15%
20 Primitive Project Ideas: Tiny Go Engines That Do the Essential 10% of Redis, Kafka and Etcd
40 Projects Worth Building: SQLite for X, Tiny Infrastructure, MCP Tools and Edge Systems
40 Radically Different Infrastructure Primitives, From Reach and Expect to Ignorance and Stop
Counterfactual Store vs. Markov Chains: From Branching State to Reach, an Engine for Possible Futures
Counterfactual Store: A Database That Stores Alternatives, Not Just Facts
Mobile App Performance: The Five Metrics That Decide Retention and Store Ratings
Screening 20 Infrastructure Primitives Money First: Why Distill and Precomputing Survive
Temporal KV: A Key-Value Store That Remembers History
A Background Job Queue in One SQLite File Covers What Most Apps Deploy Redis For

Media Partners

  • AltSql.com
  • Technology Conferences
  • API Coding
AltSql Is a Native Hybrid of Key-Value and SQL, From the Sensor to the Gateway
AltSql Core and AltSql DB Are Now Open Source Under the Apache License 2.0
Introduction
AltSql DB 0.3 Adds Secondary Indexes and Statement Savepoints: A Lookup on a Million Rows Ran 198 Times Faster Than a Full Scan
How It Works
AltSql DB 0.2: SQL and Direct Calls Wrote Byte-Identical Files Over 100,000 Random Steps
AltSql DB Keeps a Whole Fleet in One File and Reads by Key 5 Times Faster Than SQLite Through SQL
AltSql Core and Six Prototypes Built Around It
AltSql Ask Puts One SQL Question to 500 Simulated Machines and Brings Back Only the Answers
Machine Monitoring Case Study: Overheat Alarm Handled on the Sensor While Wi-Fi Was Down
SoftDevStudio.com at Web Summit 2026, November 9-12, MEO Arena and FIL, Lisbon
Bodor Laser Brings Integrated Tube Processing to EuroBLECH 2026
Cloudflare Connect 2026 Reportage, October 19-21, Moscone West, San Francisco
International Test Conference 2026, October 11–16, Grand Hyatt San Antonio River Walk, San Antonio
AUSA Annual Meeting & Exposition 2026, October 12–14, Walter E. Washington Convention Center, Washington DC
SEMICON West 2026, October 13–15, Moscone Center, San Francisco
Fal.Con Europe 2026, November 2–4, Fira Gran Via, Barcelona
A3 International Robot Safety Conference 2026, November 3–5, Huntington Place, Detroit
Humanoids Summit Silicon Valley 2026, December 1–2, San Mateo County Event Center, San Mateo
Sohn London Investment Conference 2026, November 18, London Marriott Grosvenor Square, London
Idempotency Keys: How One Header Stops a Retry From Charging a Customer Twice
A Tiny ETL Binary Competes With curl, jq and SQLite in a Cron Job, So Build It That Small
An AI Agent Flight Recorder Belongs in One Portable File, the Way HAR Did It for HTTP
Benchmarking MCP Servers and Stateful API Workflows: Latency, Throughput and Tokens per Call
Diagnose a Slow API From One Request: DNS, Connect, TLS, Server Wait and Transfer
Finding API Endpoints, Tables and Flags Nobody Uses Takes Code and Traffic Together
Fuzzing MCP Servers: Generate Bad Arguments From the Tool Schema and Watch What Breaks
Give Any API a History: Poll It, Hash It and Query Old Versions With SQL
Infer Your API's Real Contract From Traffic, Then Diff It Against the Docs
Keeping Third-Party API Responses in SQLite Gets You a Cache, an Offline Mode and a History

Copyright © 2026 Technologies.org

Media Partners: Market Analysis · Market Research · Referently · Photography