Face 31

[Shawana Kallhoff]

Ourmildest cleanser specifically formulated for daily facial use. Helps remove makeup and excess skin oils without drying your skin. Leaves skin feeling clean and soft. Ideal for dry skin. Now available in a convenient 2.5 ounce travel size!

A mild and gentle cleansing bar for daily use on face, hands, and body. Leaves your skin feeling soft and moisturized. Ideal for dry skin associated with atopic dermatitis (eczema), psoriasis, and winter itch.

Helps restore and maintain a normal moisture level. Soothes red, irritated, cracking or itchy skin. Ideal moisturizing formula for dry skin associated with atopic dermatitis (eczema), psoriasis, ichthyosis, and winter itch.

Our maximum strength over the counter (OTC) 1% hydrocortisone anti-itch cream provides fast relief for flare-ups due to eczema, dermatitis, and psoriasis. Effective relief from itching associated with minor skin irritations, inflammation, and rashes due to jewelry, soaps, detergents, cosmetics, insect bites, and poison ivy, oak, and sumac. Temporary relief of external genital and anal itching.

OUR FARM JOURNEYSome might say it all started with a crooked face cow. Though truly, the devotion to cheese craftsmanship and to local dairy farms began shortly after Amy Rowbottom was born to a milk making family in Maine. More >

OUR FARM TO YOUR DOORAll cheeses are handcrafted with high quality whole milk, no preservatives, and limited ingredients, and often specially cold-smoked, for the creamiest, richest flavor and texture. Shop now > Find locally >

OUR CHEESE STORYBetween visits to local dairy farms to scratch beloved cow noses, Amy is now hard at work creating a unique mix of award winning cheeses for her Crooked Face Creamery and Up North Cheese brands. More >

NIST has published NISTIR 8331 - Ongoing FRVT Part 6B: Face recognition accuracy with face masks using post-COVID-19 algorithms on November 30, 2020, the second out of a series of reports aimed at quantifying face recognition accuracy for people wearing masks. This report adds 1) 65 new algorithms submitted to FRVT 1:1 since mid-March 2020 (and includes cumulative results for 152 algorithms evaluated to date) and 2) assessment of when both the enrollment and verification images are masked (in addition to when only the verification image is masked). Our initial approach has been to apply masks to faces digitally (i.e., using software to apply a synthetic mask). This allowed us to leverage large datasets that we already have. This report quantifies the effect of masks on both false negative and false positives match rates. For more information, visit the FRVT Face Mask Effects webpage.

NIST describes and quantifies demographic differentials for contemporary face recognition algorithms in this report, NISTIR 8280. NIST has conducted tests to quantify demographic differences for nearly 200 face recognition algorithms from nearly 100 developers, using four collections of photographs with more than 18 million images of more than 8 million people.

The FRVT Ongoing activity is conducted on a continuing basis and will remain open indefinitely such that developers may submit their algorithms to NIST whenever they are ready. This approach more closely aligns evaluation with development schedules. The evaluation will use very large sets of facial imagery to measure the performance of face recognition algorithms developed in commercial and academic communities worldwide. Multiple evaluation tracks relevant to face recognition will be conducted under this test. For more information, visit the FRVT Ongoing webpage.

The FRVT 1:N 2018 will measure advancements in the accuracy and speed of one-to-many face recognition identification algorithms searching enrolled galleries containing at least 10 million identities. The evaluation will primarily use standardized portrait images, and will quantify how accuracy depends on subject-specific demographics and image-specific quality factors. For more information, visit the FRVT 1:N 2018 webpage.

Facial morphing and the ability to detect it is an area of high interest to a number of photo-credential issuance agencies and those employing face recognition for identity verification. The FRVT MORPH test will provide ongoing independent testing of prototype facial morph detection technologies.

NIST is establishing an evaluation of face image quality assessment algorithms. NIST will run quality assessment algorithms on large sets of images and relate their outputs to face recognition outcomes.

While not part of the FRVT series, the Face-in-Video-Evaluation (FIVE) conducted 2015-2016 will be of interest to the FRVT audience. The FIVE activity assessed face recognition capability in video sequences. The outcomes of FIVE were published in NIST Interagency Report 8173.

In conjunction with IARPA, NIST ran its first Face Recognition Prize Challenge (FRPC) to assess capability of the latest algorithms operating on unconstrained images. IARPA awarded cash prizes to the most accurate identification and verification algorithms.

The Face Recognition Algorithm Independent Evaluation (CHEXIA-FACE) was conducted to assess the capability of face detection and recognition algorithms to correctly detect and recognize children's faces appearing in unconstrained imagery.

FRVT 2013 tested state-of-the-art face recognition performance. It used very large sets of facial imagery to measure the accuracy and computational efficiency of face recognition algorithms developed in commercial and academic communities worldwide. The test itself ran from July 2012 to the end of 2013. The detailed plans, procedures and outcomes of the test are documented on the FRVT 2013 homepage.

Under the name MBE 2010, 2D face recognition algorithms were evaluated, yielding two reports. First, NIST Interagency Report 7709 gave results for both verification and identification algorithms. Second, the NIST Interagency Report 7830 surveyed compression and resolution parameters for storing face images on identity credentials.

The FRVT 2006 measured performance with sequestered data (data not previously seen by the researchers or developers). A standard dataset and test methodology was employed so that all participants were evenly evaluated. The government provided both the test data and the test environment to participants. The test environment was called the Biometric Experimentation Environment (BEE). The BEE was the FRVT 2006 infrastructure. It allowed the experimenter to focus on the experiment by simplifying test data management, experiment configuration, and the processing of results.

FRVT 2002 consisted of two tests: the High Computational Intensity (HCInt) Test and the Medium Computational Intensity (MCInt) Test. Both test required the systems to be full automatic, and manual intervention was not allowed.

FRVT 2000 consisted of two components: the Recognition Performance Test and the Product Usability Test. The Recognition Performance Test was a technology evaluation. The goal of the Recognition Performance Test was to compare competing techniques for performing facial recognition. All systems were tested on a standardized database. The standard database ensured all systems were evaluated using the same images, which allowed for comparison of the core face recognition technology. The product usability test examined system properties for performing access control.

The goal of the FERET program was to develop automatic face recognition capabilities that could be employed to assist security, intelligence, and law enforcement personnel in the performance of their duties. The task of the sponsored research was to develop face recognition algorithms. The FERET database was collected to support the sponsored research and the FERET evaluations. The FERET evaluations were performed to measure progress in algorithm development and identify future research directions.

Millions of men experience depression, but far fewer seek help. The Face It Foundation gives men the support they need to face depression, take control of their recovery and get their lives back. The generous donations of organizations and individuals ensure that our services and resources are free for the men who need them.

Please join us on Monday, September 9, 2024 at the Majestic Oaks Golf Club in Ham Lake, MN for a fun day of golf, friendship, laughs, really great food, amazing silent auction and raffle prizes, and most importantly supporting the work of the Face It Foundation.

Face or touch unlock works best on the following devices and browsers, especially with combinations that match between device and browser. If you are using Firefox and cannot authenticate with face or touch unlock, switch to using Safari if on an Apple device or Chrome if on a Windows or Android device.

We strongly recommend adding a second authentication method in case you replace or lose your device. If you lose access to your only authentication method, you will need to delete your account and create a new one.

Face or touch unlock will only work on the original device you set it up with unless you set up face or touch unlock on a newer device and browser that supports passkeys, and has bluetooth or cloud sync between your accounts enabled. Having bluetooth or cloud sync enabled allows your face or touch unlock credential to be shared between your devices.

To prevent having to delete your account in the future, we strongly recommend setting up more than one authentication method. That way, you have a back-up authentication method to use for signing in in case you lose one.

We have chosen to partner with Reforest Now, a non-profit environmental NGO established in 2018 and based in Northern NSW, Australia. Their mission is to return rainforest back to the land where it once stood and to protect existing rainforests of Australia and the rich ecosystems within by growing and planting trees.

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