Abstract: Methods, devices, and systems related to determining biometric data using an array of infrared (IR) illuminators are described. In an example, a method can include projecting a number of IR dots on a user using a dot projector and an array of IR illuminators, capturing an IR image of the number of IR dots using an IR camera, comparing a number of pixels of the captured IR image to a number of corresponding pixels of a baseline IR image using a processing resource, and determining biometric data of the user at least partially based on comparing the captured IR image to the baseline IR image using the processing resource.

Abstract: Methods, devices, and systems related to a computing device for displaying an AR responsive to an input are described. An input can include, but is not limited to, a timestamp, weather data, event data, a rating, a user preference, a user input, or a location. In an example, a method can include receiving an input at an AR platform of a computing device from a processing resource of the computing device, receiving an image at the AR platform from a camera of the computing device, comparing the image to a number of AR images included on the AR platform, determining at the AR platform that the image is an AR image of the number of AR images, receiving at a user interface an AR associated with the AR image from the AR platform, and displaying the AR on the user interface in response to receiving the AR.

Abstract: Methods, apparatuses, and systems associated with anomaly detection and resolution are described. Examples can include detecting, via a sensor of a robot, an object in a path of the robot while the robot is performing a task in an environment and classifying the object as an anomaly or a non-anomaly and the environment as anomalous or non-anomalous using a machine learning model. Examples can include proceeding with the task responsive to classification of the object as a non-anomaly and the environment as non-anomalous and resolving the anomaly or the anomalous environment and proceeding with the task responsive to classification of the object as an anomaly or the environment as anomalous.

Abstract: Methods, devices, and systems related to a computing device for displaying an AR responsive to an AR image are described. In an example, a method can include receiving first signaling including data representing an image at an AR platform of a computing device from a camera, comparing the data representing the image to data representing a number of AR images included on the AR platform, determining that the image is an AR image of the number of AR images in response to a particular portion of the data representing the image matching data representing the AR image, receiving at a user interface of the computing device second signaling including data representing an AR associated with the AR image in response to determining the image is the AR image, and displaying the data representing the AR on the user interface in response to receiving the second signaling.

Abstract: An example method can include receiving at least one of: a product dimension, a product review, a product material, a product color, a product fit, a product style, product manufacturing data, product manufacturer, a product image, or a product three-dimensional (3-D) image at an AI accelerator, receiving at least one of: a user input or user data at the AI accelerator, generating one or more recommended products responsive to the AI accelerator performing an AI operation on at least one of: the product dimension, the product review, the product material, the product color, the product fit, the product style, the product manufacturing data, the product manufacturer, the product image, or the product 3-D image and at least one of: the user input or the user data using the AI model, and display the one or more recommended products on a user interface.

Abstract: Systems, apparatuses, and methods related to media type selection are described. Memory systems can include multiple types of memory media (e.g., volatile and/or non-volatile) and can write data to the memory media types. Data inputs can be written (e.g., stored) in a particular type of memory media based on characteristics (e.g., source, attributes, and/or information etc. included in the data). For instance, selection of memory media can be based on characteristics of the memory media type and the attributes of the data input. In an example, a method can include receiving, by a memory system that comprises a plurality of memory media types, data from at least one of a plurality of sensors, identifying one or more attributes of the data; and selecting, based at least in part on the one or more attributes of the data, one or more of the memory media types to write the data to.

Abstract: Methods and devices related to reduced diffraction micro lens imaging are described. In an example, a method can include receiving light, via an array of micro lenses including embedded optics configured to reduce diffraction relative to a threshold value associated with another array of micro lenses without embedded optics, at an array of image sensors coupled to the array of micro lenses and positioned to receive the light in response to the light passing through the array of micro lenses, and generating an image from the light at the array of image sensors based at least in part on reduced diffraction of the light.

Abstract: Methods and devices related to actuating an image sensor are described. In an example, a method can include generating a first image of an area at a first time using an array of image sensors, wherein each image sensor of the array of image sensors is coupled to a respective actuator, generating a second image of the area at a second time using the array of image sensors, comparing the first image to the second image using a processing resource coupled to the array of image sensors, identifying a moving object based at least in part on comparing the first image to the second image, and activating the actuator for each image sensor of the array of image sensor used to generate the first and second images based at least in part on identifying the moving object.

Abstract: Embodiments of the present disclosure include apparatuses and methods for stacked polarizer hyperspectral imaging. In a number of embodiments, a method can include passing a light source input through a lens and a hyperspectral sensor, activating a first polarization layer of a plurality of polarization layers, detecting a first hyperspectral image with an array of pixels from the light source input that is polarized when passed through the first polarization layer, and determining, via a controller coupled to the array of pixels, whether a quality of the first hyperspectral image that was polarized by the first polarization layer meets a threshold. A stacked polarizer can include a plurality of polarizers that are stacked upon each other such that a hyperspectral light source input can be pass through the stack of polarizers and be detected by a pixel of an image sensor cell. Each of the polarizers in the stack of polarizers can be individually activated and deactivated.

Abstract: Embodiments of the present disclosure include apparatuses and method for stacked polarizer imaging. In a number of embodiments, a method can include activating a first polarization layer of a plurality of polarization layers, detecting a first image with an array of pixels from a light source input that is polarized when passed through the first polarization layer, and determining, via a controller coupled to the array of pixels, whether a quality of the first image that was polarized by the first polarization layer meets a threshold. A stacked polarizer can include a plurality of polarizers that are stacked upon each other such that a light source input can be passed through the stack of polarizers and be detected by a pixel of an image sensor cell. Each of the polarizers in the stack of polarizers can be individually activated and deactivated.

Abstract: Systems, apparatuses, and methods related to image based media type selection are described. Memory systems can include multiple types of memory media (e.g., volatile and/or non-volatile). Determinations of which memory media types to write image data to can be made and the data can be written (e.g., stored) in the determined type of memory media. A determined memory media type can be based on attributes of the data. In an example, a method can include receiving, by a memory system that comprises a plurality of memory media types, initial image data from an image sensor coupled to the memory system, identifying one or more attributes of the initial image data, determining a type of memory media to write the initial image data to based on the identified attributes of the initial image data, and selecting, based at least in part on the determined type of memory media, a first memory type of the plurality of memory media types to write the initial image data.

Abstract: Systems, apparatuses, and methods related to image based media type selection are described. Memory systems can include multiple types of memory media. Data can be written in a type of memory media based on one or more settings applied to the data. A setting can be determined based on input received by a logic within the memory system. In an example, a method can include receiving, at logic within a memory system that comprising a plurality of memory media types, data from an image sensor coupled to the logic of the memory system, receiving input from a host, identifying one or more attributes of the data, analyzing the received input to determine an setting, generating the setting based on the analyzed input, and writing the data to a first memory media type of the plurality of memory media types based on the generated setting.

Abstract: Methods, apparatuses, and non-transitory machine-readable media for displaying information and/or images on a display of a computing device based on received data. Apparatuses can include a display screen, a memory resource, a recognition sensor, and a controller. An example controller can receive data and activate information and/or images on a display screen based in part on the received data. In another example, a method can include storing recognition data in a memory resource, receiving primary recognition data, comparing the primary recognition data to the stored recognition data, and activating the display screen for a viewing angle responsive to authentication of the primary recognition data through the comparison of the primary recognition data and the stored recognition data.

Abstract: An image or a spectrum of a surface may be acquired by a computing device, which may be included in a mobile device in some examples. The computing device may extract a measured spectrum from the image and generate a corrected spectrum of the surface. In some examples, the corrected spectrum may be generated to compensate for ambient light influence. The corrected spectrum may be analyzed to provide a result, such as a diagnosis or a product recommendation. In some examples, the result is based, at least in part, on a comparison of the corrected spectrum to reference spectra. In some examples, the result is based, at least in part, on an inference of a machine learning model.

Abstract: Methods, devices, and systems related to a computing device for capturing an augmented reality (AR) image displaying an AR are described. An example method can include projecting a structured array of light, from a mobile device, onto an object. The method further includes measuring multi-directional sections of the object with the projected light. The method further includes reconstructing a three-dimensional (3D) figure of the object based on the measured multi-directional sections. The method further includes displaying an augmented reality (AR) image associated with the 3D figure on a user interface of the mobile device.

Abstract: Methods, devices, and systems related to a computing device for capturing and displaying an augmented reality (AR) image are described. An example method can include capturing a first three-dimensional (3D) figure of a user at a mobile device. The method further includes accessing the first 3D figure of a user at the mobile device. The method further includes receiving, at the mobile device, a selection of a product to display on the 3D figure. The method further includes displaying, on the mobile device, the product to display on the first 3D figure as an augmented reality (AR) image.

Abstract: Systems, apparatuses, and methods related to audio input prioritization are described. Systems may include to one or more sound devices. Audio input may be played on a sound device based on one or more settings applied to the audio input. A setting can be determined based on feedback received by a host. In an example, a method for prioritizing audio input may include receiving a plurality of audio inputs each comprising signaling representative of different sounds, and each from a different application, identifying an attribute of each audio input of the plurality of audio inputs, prioritizing each audio input based on the identified attribute of each audio input, and sending each audio input to a sound device to be played based on the prioritization.

Abstract: Embodiments of the present disclosure include apparatuses and methods for sensor blocking. In a number of embodiments, a method can include operating a sensor block of an apparatus in a first mode to allow a sensor to receive inputs, and operating the sensor block in a second mode to inhibit the sensor from receiving the inputs. A sensor block can be used to prevent a sensor, such as an image sensor, from receiving an input, such as a light source input, to capture image data. A sensor block can be used to prevent a sensor from capturing image data even when an application causing to the sensor to operate, such as when applications have access to the sensor, but the user of a device is unaware that an application is using the sensor. The sensor block can be used to prevent the sensor from capturing useful images and the sensor can only capture a black image of the sensor block and not the surroundings of the device.

Abstract: Methods and apparatuses related to access to data stored in quarantined memory media are described. Memory systems can include multiple types of memory media (e.g., volatile and/or non-volatile) and data (e.g., information included in) stored in the memory media often are subject to risks of the data being undesirably exposed to the public. For example, requests to write data in the memory media can often be made and accepted without a user's awareness, which can lead to the undesirable exposure of the data. According to embodiments of the present disclosure, a particular portion and/or location in the memory media can provide a data protection scheme such that data stored in the particular location can be refrained from being transferred out of the computing system.

Abstract: Methods, apparatuses, and non-transitory machine-readable media for image location based on a perceived interest are described. Apparatuses can include a display, a memory device, and a controller. In an example, the controller can assign a perceived interest and sort images based in part on the perceived interest. In another example, a method can include the assigning, by a controller coupled to a memory device, a perceived interest of an image of a plurality of images, wherein the perceived interest is assigned based in part on a period of time the image is visible on a display coupled to the memory device, selecting the image from an initial viewing location responsive to the assigned perceived interest; and transferring the image to a different viewing location, wherein the initial viewing location and the different viewing location are visible on the display.