Abstract: The disclosure relates to systems and methods for real-time detection of a very large number of items in a given constrained volume. Specifically, the disclosure relates to systems and methods for retrieving an optimized set of classifiers from a self-updating classifiers' database, configured to selectively and specifically identify products inserted into a cart in real time, from a database comprising a large number of stock-keeping items, whereby the inserted items' captured images serve simultaneously as training dataset, validation dataset and test dataset for the recognition/identification/re-identification of the product.

Abstract: Al-based computer vision algorithms, operating in the real world rather than in the digital domain, typically operate in a certain three-dimensional space. The system, programs and method provided herein, describe a system that allows limiting the execution of Al algorithms to operate only on objects breaching a predefined and confined plane (also termed grid) or a volume in space. In other words, the system programs and method provided herein define a 2D/2.5D/3D regions or grid in space, operable to detect any change which occurs in and through this grid. This ability includes in certain implementations, the detection of any animate or inanimate object, or multiple grouped objects which may cross, pass or introduced to this grid, their type, identification and action assigning.

Abstract: An indoor autonomous aerial system and method that uses micro aerial vehicle/s (MAV/s). Said system is configured to be deployable and operable in reduced GPS signal reception expansive spaces and the MAV/s is/are configured to be automatically guided and perform tasks at desired location/s, transmit/receive data, present various signs, etc. Said system and method can be used for various purposes such as, advertisement, inventory management, guidance, warning, search and rescue, etc.

Abstract: The disclosure relates to systems and methods for real-time detection of a very large number of items in a given constrained volume. Specifically, the disclosure relates to systems and methods for retrieving an optimized set of classifiers from a self-updating classifiers' database, configured to selectively and specifically identify products inserted into a cart in real time, from a database comprising a large number of stock-keeping items, whereby the inserted items' captured images serve simultaneously as training dataset, validation dataset and test dataset for the recognition/identification/re-identification of the product.

Abstract: The disclosure is directed to system, methods and programs for automatic verification and validation of users' actions during assembly of products intended for purchase in a shopping cart, more specifically, the disclosure is directed to systems, methods and programs for automatically validating correct identification and markings of items inserted to an artificially intelligent shopping cart by using action-recognition associated with correct scanning/presentation of the item to a product recognition module coupled to the artificially intelligent shopping cart.

Abstract: The disclosure relates to systems and methods for real-time detection of a very large number of items in a given constrained volume. Specifically, the disclosure relates to systems and methods for retrieving an optimized set of classifiers from a self-updating classifiers' database, configured to selectively and specifically identify products inserted into a cart in real time, from a database comprising a large number of stock-keeping items, whereby the inserted items' captured images serve simultaneously as training dataset, validation dataset and test dataset for the recognition/identification/re-identification of the product.

Abstract: The disclosure relates to systems and methods for automatic detection of product insertion and product extraction in an Artificial Intelligent Cart (AIC). Specifically, the disclosure relates to systems and methods of ascertaining insertion and extraction of product into and from an open shopping cart, by continuously monitoring triggered content changes.

Abstract: The disclosure relates to systems and methods for automatic detection of product insertion and product extraction in an Artificial Intelligent Cart (AIC). Specifically, the disclosure relates to systems and methods of ascertaining insertion and extraction of product into and from an open shopping cart, by continuously monitoring triggered content changes.

Abstract: The disclosure relates to systems and methods for real-time detection of a very large number of items in a given constrained volume. Specifically, the disclosure relates to systems and methods for retrieving an optimized set of classifiers from a self-updating classifiers' database, configured to selectively and specifically identify products inserted into a cart in real time, from a database comprising a large number of stock-keeping items, whereby the inserted items' captured images serve simultaneously as training dataset, validation dataset and test dataset for the recognition/identification/re-identification of the product.