Patents by Inventor Daniel Matthew Merl
Daniel Matthew Merl has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
-
Publication number: 20230028553Abstract: In an industrial control system (ICS), latent vectors are generated to represent identity or behaviors of host devices coupled to the ICS. A computing system captures communications transmitted by a host device across a network associated with the ICS. A set of values are extracted from one or more respective fields in the communication, then applied to a trained neural network. Values of a first set of fields are applied at an input layer of the trained neural network, while values of a second set of fields are applied at an output layer of the neural network. Based on the application of the neural network to the values extracted from the communication, the computing system generates a latent vector.Type: ApplicationFiled: July 8, 2022Publication date: January 26, 2023Inventors: Brian Michael Kelley, Indrasis Chakraborty, Brian James Gallagher, Daniel Matthew Merl
-
Patent number: 11557215Abstract: An exercise feedback system receives exercise data such as images or video captured by client devices of users performing exercises. The exercise feedback system may access a machine learning model trained using image of a population of users. The images used for training may be labeled, for example, as having proper or improper musculoskeletal form. The exercise feedback system may determine a metrics describing the musculoskeletal form of a user by applying the trained machine learning model to images of the user as input features. The exercise feedback system may generate feedback for a certain exercise using the metrics based on output predictions of the model. The feedback can be provided to a client device of the user or a physical therapist for presentation.Type: GrantFiled: August 7, 2018Date of Patent: January 17, 2023Assignee: Physera, Inc.Inventors: Yigal Dan Rubinstein, Cameron Marlow, Todd Riley Norwood, Jonathan Chang, Shane Patrick Ahern, Daniel Matthew Merl
-
Patent number: 11183079Abstract: An exercise feedback system receives exercise data captured by client devices of users performing musculoskeletal exercises. The exercise feedback system may provide captured images to a client device of a physical trainer (PT) who remotely provides feedback on the users' exercise performances, for example, by labeling images as indicative of proper or improper musculoskeletal form. A PT may track multiple users using a central feed, which includes content displayed in an order based on ranking of users by a model. Additionally, the exercise feedback system may provide an augmented reality (AR) environment. For instance, an AR graphic indicating a target musculoskeletal form for an exercise is overlaid on a video feed displayed by a client device. Responsive to detecting that a user's form is aligned to the AR graphic, the exercise feedback system may notify the user and trigger the start of the exercise.Type: GrantFiled: March 21, 2018Date of Patent: November 23, 2021Assignee: Physera, Inc.Inventors: Yigal Dan Rubinstein, Cameron Marlow, Todd Riley Norwood, Jonathan Chang, Shane Ahern, Daniel Matthew Merl
-
Patent number: 10929772Abstract: Systems, methods, and non-transitory computer readable media are configured to apply a machine learning model to predict an age division for a user based on user information. An age bracket within the age division including a largest number of connections of the user can be determined. The determined age bracket can be assigned for the user.Type: GrantFiled: December 20, 2016Date of Patent: February 23, 2021Assignee: Facebook, Inc.Inventors: Carlos Gregorio Diuk Wasser, Michael Lee Develin, Smriti Bhagat, Viet An Nguyen, Daniel Matthew Merl
-
Patent number: 10922997Abstract: An exercise feedback system receives exercise data captured by client devices of users performing musculoskeletal exercises. The exercise feedback system may provide captured images to a client device of a physical trainer (PT) who remotely provides feedback on the users' exercise performances, for example, by labeling images as indicative of proper or improper musculoskeletal form. A PT may track multiple users using a central feed, which includes content displayed in an order based on ranking of users by a model. Additionally, the exercise feedback system may provide an augmented reality (AR) environment. For instance, an AR graphic indicating a target musculoskeletal form for an exercise is overlaid on a video feed displayed by a client device. Responsive to detecting that a user's form is aligned to the AR graphic, the exercise feedback system may notify the user and trigger the start of the exercise.Type: GrantFiled: March 21, 2018Date of Patent: February 16, 2021Assignee: Physera, Inc.Inventors: Yigal Dan Rubinstein, Cameron Marlow, Todd Riley Norwood, Jonathan Chang, Shane Ahern, Daniel Matthew Merl
-
Patent number: 10902741Abstract: An exercise feedback system receives exercise data captured by client devices of users performing musculoskeletal exercises. The exercise feedback system may provide captured images to a client device of a physical trainer (PT) who remotely provides feedback on the users' exercise performances, for example, by labeling images as indicative of proper or improper musculoskeletal form. A PT may track multiple users using a central feed, which includes content displayed in an order based on ranking of users by a model. Additionally, the exercise feedback system may provide an augmented reality (AR) environment. For instance, an AR graphic indicating a target musculoskeletal form for an exercise is overlaid on a video feed displayed by a client device. Responsive to detecting that a user's form is aligned to the AR graphic, the exercise feedback system may notify the user and trigger the start of the exercise.Type: GrantFiled: March 21, 2018Date of Patent: January 26, 2021Assignee: Physera, Inc.Inventors: Yigal Dan Rubinstein, Cameron Marlow, Todd Riley Norwood, Jonathan Chang, Shane Ahern, Daniel Matthew Merl
-
Publication number: 20200051446Abstract: An exercise feedback system receives exercise data such as images or video captured by client devices of users performing exercises. The exercise feedback system may access a machine learning model trained using image of a population of users. The images used for training may be labeled, for example, as having proper or improper musculoskeletal form. The exercise feedback system may determine a metrics describing the musculoskeletal form of a user by applying the trained machine learning model to images of the user as input features. The exercise feedback system may generate feedback for a certain exercise using the metrics based on output predictions of the model. The feedback can be provided to a client device of the user or a physical therapist for presentation.Type: ApplicationFiled: August 7, 2018Publication date: February 13, 2020Inventors: Yigal Dan Rubinstein, Cameron Marlow, Todd Riley Norwood, Jonathan Chang, Shane Patrick Ahern, Daniel Matthew Merl
-
Publication number: 20190295436Abstract: An exercise feedback system receives exercise data captured by client devices of users performing musculoskeletal exercises. The exercise feedback system may provide captured images to a client device of a physical trainer (PT) who remotely provides feedback on the users' exercise performances, for example, by labeling images as indicative of proper or improper musculoskeletal form. A PT may track multiple users using a central feed, which includes content displayed in an order based on ranking of users by a model. Additionally, the exercise feedback system may provide an augmented reality (AR) environment. For instance, an AR graphic indicating a target musculoskeletal form for an exercise is overlaid on a video feed displayed by a client device. Responsive to detecting that a user's form is aligned to the AR graphic, the exercise feedback system may notify the user and trigger the start of the exercise.Type: ApplicationFiled: March 21, 2018Publication date: September 26, 2019Inventors: Yigal Dan Rubinstein, Cameron Marlow, Todd Riley Norwood, Jonathan Chang, Shane Ahern, Daniel Matthew Merl
-
Publication number: 20190295437Abstract: An exercise feedback system receives exercise data captured by client devices of users performing musculoskeletal exercises. The exercise feedback system may provide captured images to a client device of a physical trainer (PT) who remotely provides feedback on the users' exercise performances, for example, by labeling images as indicative of proper or improper musculoskeletal form. A PT may track multiple users using a central feed, which includes content displayed in an order based on ranking of users by a model. Additionally, the exercise feedback system may provide an augmented reality (AR) environment. For instance, an AR graphic indicating a target musculoskeletal form for an exercise is overlaid on a video feed displayed by a client device. Responsive to detecting that a user's form is aligned to the AR graphic, the exercise feedback system may notify the user and trigger the start of the exercise.Type: ApplicationFiled: March 21, 2018Publication date: September 26, 2019Inventors: Yigal Dan Rubinstein, Cameron Marlow, Todd Riley Norwood, Jonathan Chang, Shane Ahern, Daniel Matthew Merl
-
Publication number: 20190295438Abstract: An exercise feedback system receives exercise data captured by client devices of users performing musculoskeletal exercises. The exercise feedback system may provide captured images to a client device of a physical trainer (PT) who remotely provides feedback on the users' exercise performances, for example, by labeling images as indicative of proper or improper musculoskeletal form. A PT may track multiple users using a central feed, which includes content displayed in an order based on ranking of users by a model. Additionally, the exercise feedback system may provide an augmented reality (AR) environment. For instance, an AR graphic indicating a target musculoskeletal form for an exercise is overlaid on a video feed displayed by a client device. Responsive to detecting that a user's form is aligned to the AR graphic, the exercise feedback system may notify the user and trigger the start of the exercise.Type: ApplicationFiled: March 21, 2018Publication date: September 26, 2019Inventors: Yigal Dan Rubinstein, Cameron Marlow, Todd Riley Norwood, Jonathan Chang, Shane Ahern, Daniel Matthew Merl
-
Patent number: 10180935Abstract: A system for identifying language(s) for content items is disclosed. The system can identify different languages for content item words segments by identifying segment languages that maximize a probability across the segments. The probability can be a combination of: an author's likelihood for the language identified for the first word; a combination of transition frequencies for selected languages identified for words, the transition frequencies indicating likelihoods that a transition occurred to the selected language from the previous word's language; and a combination of observation probabilities indicating, for a given word in the content item, a likelihood the given word is in the identified language. For an in-vocabulary word, the observation probabilities can be based on learned probability for that word. For an out-of-vocabulary word, the probability can be computed by breaking the word into overlapping n-grams and computing combined learned probabilities that each n-gram is in the given language.Type: GrantFiled: February 2, 2017Date of Patent: January 15, 2019Assignee: Facebook, Inc.Inventors: Daniel Matthew Merl, Aditya Pal, Stanislav Funiak, Seyoung Park, Fei Huang, Amac Herdagdelen
-
Publication number: 20180189259Abstract: A system for identifying language(s) for content items is disclosed. The system can identify different languages for content item words segments by identifying segment languages that maximize a probability across the segments. The probability can be a combination of: an author's likelihood for the language identified for the first word; a combination of transition frequencies for selected languages identified for words, the transition frequencies indicating likelihoods that a transition occurred to the selected language from the previous word's language; and a combination of observation probabilities indicating, for a given word in the content item, a likelihood the given word is in the identified language. For an in-vocabulary word, the observation probabilities can be based on learned probability for that word. For an out-of-vocabulary word, the probability can be computed by breaking the word into overlapping n-grams and computing combined learned probabilities that each n-gram is in the given language.Type: ApplicationFiled: February 2, 2017Publication date: July 5, 2018Inventors: Daniel Matthew Merl, Aditya Pal, Stanislav Funiak, Seyoung Park, Fei Huang, Amac Herdagdelen