In an example method, a series of time-based clustering images is generated for a plurality of library fragments from a genome sample. Each time-based clustering image in the series is sequentially generated. To generate each time-based clustering image in the series: i) a respective sample is introduced to a flow cell, the respective sample including contiguity preserved library fragments of the plurality of library fragments, wherein the contiguity preserved library fragments are attached to a solid support or are attached to each other; ii) the contiguity preserved library fragments are released from the solid support or from each other; iii) the contiguity preserved library fragments are amplified to generate a plurality of respective template strands; iv) the respective template strands are stained; and v) the respective template strands are imaged.

In an example method, a series of time-based clustering images is generated for a plurality of library fragments from a genome sample. Each time-based clustering image in the series is sequentially generated. To generate each time-based clustering image in the series: i) a respective sample is introduced to a flow cell, the respective sample including contiguity preserved library fragments of the plurality of library fragments, wherein the contiguity preserved library fragments are attached to a solid support or are attached to each other; ii) the contiguity preserved library fragments are released from the solid support or from each other; iii) the contiguity preserved library fragments are amplified to generate a plurality of respective template strands; iv) the respective template strands are stained; and v) the respective template strands are imaged.

Methods, systems, and computer-readable storage media for processing images captured in a retail store and automatically identifying a product shortage are provided. In one implementation, a system may access information describing a desired placement of products on at least one store shelf. The system may analyze a first image captured at a first time to determine that a first quantity of products exceeds a quantity threshold. The system may analyze a second image captured at a second time later than the first time to determine that a second quantity of products is below the quantity threshold. The system may avoid initiating an unscheduled action to cause restocking until a third time later than the second time. Based on a determination that a third quantity of products at the third time are below the quantity threshold, the system may provide information indicative of a product shortage.

Methods, systems, and apparatus including computer programs encoded on a computer storage medium, for retrieving image search results using embedding neural network models. In one aspect, an image search query is received. A respective pair numeric embedding for each of a plurality of image-landing page pairs is determined. Each pair numeric embedding is a numeric representation in an embedding space. An image search query embedding neural network processes features of the image search query and generates a query numeric embedding. The query numeric embedding is a numeric representation of the image search query in the same embedding space. A subset of the image-landing page pairs having pair numeric embeddings that are closest to the query numeric embedding of the image search query in the embedding space are identified as first candidate image search results.

A computing system that can receive an object search request from a user indicating a request to search for a specific object in an area traversed by one or more autonomous vehicle. The object search request can include a set of physical characteristics of the specific object. The computing system can then transmit a signal to an autonomous vehicle indicating a request for the autonomous vehicle to search for the specific object. The signal can cause the autonomous vehicle to transmit an image, selected based on a physical characteristic of the object, to the computing system. The computing system can then generate a score indicative of a difference between one or more physical characteristic of the object in the image and the specific object. The computing system can then selectively transmit the image to a mobile device operated by the user based on the score.

A system and method for data transmission and appliance communication is provided. The system is configured to obtain a food identifier input and a preparation instruction input, generate a database correlating the food identifier input to the preparation instruction input, capture an image of food to be prepared, transmit the image of food to be prepared to a computing system, compare, at the computing system, the captured image to the database, and determine a preparation instruction corresponding to the captured image.

Provided are a system and method associated with managing contents using a computing device, wherein the method includes accessing a content entry from a content source; adding at least one of a tag, a memo, or a contact for association with the content entry; posting the at least one of the tag, the memo, or the contact in association with a link to the content entry, as a record associated with the computing device in a database; and displaying the content entry accessed in association with the at least one of the tag, the memo, or the contact as posted.

A method includes acquiring a plurality of images of a subject, acquiring a set of criteria for a profile image of the subject, and generating a new image of the subject, using the plurality of images of the subject and the set of criteria. Optionally, the method may further include selecting a first image of the plurality of images as the profile image of the subject, wherein the first image is an image of the plurality of images that best meets the set of criteria. Optionally, the method may further include generating a recommendation, where the recommendation indicates that one of: the first image or the new image should be used as the profile image for the subject.

Disclosed are a system, method and software to associate attributes with digital media assets using deep learning. Digital media contains specific assets, such as audio, that can be replaced with other assets. The system, method and software allow for personalizing digital media content based in part on neural network analysis to learn a user's emotional state.

Disclosed are a system, method and software to associate attributes with digital media assets using deep learning. Digital media contains specific assets, such as audio, that can be replaced with other assets. The system, method and software allow for personalizing digital media content based in part on neural network analysis to learn a user's emotional state.