Visual analytics tool for updating object detection models in autonomous driving applications. In one embodiment, an object detection model analysis system including a computer and an interface device. The interface device includes a display device. The computer includes an electronic processor that is configured to extract object information from image data with a first object detection model, extract characteristics of objects from metadata associated with image data, generate a summary of the object information and the characteristics, generate coordinated visualizations based on the summary and the characteristics, generate a recommendation graphical user interface element based on the coordinated visualizations and a first one or more user inputs, and update the first object detection model based at least in part on a classification of one or more individual objects as an actual weakness in the first object detection model to generate a second object detection model for autonomous driving.

Visual analytics tool for updating object detection models in autonomous driving applications. In one embodiment, an object detection model analysis system including a computer and an interface device. The interface device includes a display device. The computer includes an electronic processor that is configured to extract object information from image data with a first object detection model, extract characteristics of objects from metadata associated with image data, generate a summary of the object information and the characteristics, generate coordinated visualizations based on the summary and the characteristics, generate a recommendation graphical user interface element based on the coordinated visualizations and a first one or more user inputs, and update the first object detection model based at least in part on a classification of one or more individual objects as an actual weakness in the first object detection model to generate a second object detection model for autonomous driving.

The present disclosure relates to methods, computer readable mediums (CRMs), and systems for creating, organizing, viewing, and connecting annotations of web documents within web browsers that are made to be annotation capable. Methods, CRMs, and systems for an annotation capable web browser transmitting annotation highlighted text, annotation comment, uniform resource locator (URL), document object model (DOM) context, screenshot with marked annotation highlighted text, and annotation symbol to an annotation server are presented. Furthermore, methods, CRMs, and systems of organizing annotations within an annotation organization context area, visual queues for viewing and recognizing annotations in web documents, and a notepad for connecting annotations between web documents are presented. This disclosure relates to note taking within web documents, organizing these notes, discussing specific aspects of a web document with multiple people, and creating guided tours across multiple web documents as a reminder for oneself or for others.

A system for home clothing and footwear products arrangement includes a shelter arrangement which comprises a plurality of shelter elements for storing and sheltering a plurality of dressing items, a control center which is a computing device, an electrical terminal, a position indication arrangement for indicating a position of a target dressing item for a user, and an identifier coupled to the shelter arrangement for establishing communication between the control center and the electrical terminal, so as to allow a user to quickly find his or her target clothing or footwear product.

A system and method for managing packages may include determining an identifier on a package. A determination as to whether the package is to be positioned on a pallet based on the identifier may be made. In response to determining that the package is not to be positioned on the pallet, a first feedback signal (e.g., red light) indicative to the operator that the package is not to be placed on the pallet may be generated. In response to determining that the package is to be positioned on the pallet, a second feedback signal (e.g., green light) that is indicative to the operator that the package is to be on the pallet may be generated or no signal may be generated. Additionally, if an identifier cannot be read from the package, then a third feedback signal (e.g., yellow light) may be generated and illuminated on the package or elsewhere.

A system and method for managing packages may include determining an identifier on a package. A determination as to whether the package is to be positioned on a pallet based on the identifier may be made. In response to determining that the package is not to be positioned on the pallet, a first feedback signal (e.g., red light) indicative to the operator that the package is not to be placed on the pallet may be generated. In response to determining that the package is to be positioned on the pallet, a second feedback signal (e.g., green light) that is indicative to the operator that the package is to be on the pallet may be generated or no signal may be generated. Additionally, if an identifier cannot be read from the package, then a third feedback signal (e.g., yellow light) may be generated and illuminated on the package or elsewhere.

A machine is configured to automatically generate listings for multiple items. For example, the machine receives, from a client device, two or more images and two or more descriptions. The two or more images depict two or more items. The two or more descriptions pertain to the two or more items. The machine matches one or more images of the two or more images to a description of the two or more descriptions. The one or more images depict an item of the two or more items. The description pertains to the item. The machine, based on the matching, generates a listing of the item. The listing includes the one or more images depicting the item, and the description pertaining to the item. The machine causes display of the listing of the item in a user interface.

A system to transparently and efficiently coordinate a process across at least two independent Picture Archiving and Communication System (PACS) to allow interoperability of the PACS to acquire, retrieve, transmit, store and/or display medical images of patients. The system includes: (1) a rule engine defining a set of transformation rules for data related to the images; (2) a data unification and transformation engine identifying and resolving any conflict of the data, and tracking and assigning a unique super-identity or super-value to the data; (3) at least one database storing a list of the data and the tracking and assignment of the super-identities or super-values; (4) a security framework that controls access to the data; and (5) a control engine performing the process steps.

A system for performing automated inspection of a sewer line using machine learning. The system comprises a inspection data database storing sewer inspection data including images and metadata associated therewith; an inspection upload module receiving and uploading the sewer inspection data to the inspection data database; and an inspection module receiving the sewer inspection data from the inspection data database and generating therefrom identification data including characteristics of the sewer line identified and categorized. The identification module uses at least one machine learning model processing the sewer inspection data and determining whether at least one sewer specific characteristic is identifiable in the images and categorizing the at least one sewer specific, using a plurality of hierarchical classes where a top class performs the determination of whether the at least one sewer specific characteristic is present and the identification thereof and lower classes perform categorization in decreasing abstraction levels.

A system for performing automated inspection of a sewer line using machine learning. The system comprises a inspection data database storing sewer inspection data including images and metadata associated therewith; an inspection upload module receiving and uploading the sewer inspection data to the inspection data database; and an inspection module receiving the sewer inspection data from the inspection data database and generating therefrom identification data including characteristics of the sewer line identified and categorized. The identification module uses at least one machine learning model processing the sewer inspection data and determining whether at least one sewer specific characteristic is identifiable in the images and categorizing the at least one sewer specific, using a plurality of hierarchical classes where a top class performs the determination of whether the at least one sewer specific characteristic is present and the identification thereof and lower classes perform categorization in decreasing abstraction levels.