The present invention relates to a rock classification method wherein at least one image (IMA) of the rock to be classified is acquired, and wherein a decision tree (ARB) classifying the rocks according to several descriptors is used, as well as a machine learning method (APP) from a rock image database (BIR). Machine learning is applied for each descriptor considered.

Disclosed is a quotation method executed by a computer, comprising: obtaining structure parameters and electrical parameters of a product (S101); constructing an external view of the product by using the structure parameters of the product, and performing similarity comparison on the external view of the product and the external view of a historical product to obtain an appearance similarity sorting (102); performing similarity comparison on the electrical parameters of the product and the electrical parameters of the historical product to obtain an electrical parameter similarity sorting (103); on the basis of the cost weights of a structural member and an electrical component and the appearance similarity sorting and the electrical parameter similarity sorting, obtaining a comprehensive sorting which is based on the structure parameters and the electrical parameters (S104); and determining, based on the comprehensive sorting, a bill of materials of the product, and calculating, based on the bill of the materials of the product, the product quotation (105).

Methods and systems for determining a network embedding include training a network embedding model using training data that includes topology information for networks and attribute information relating to vertices of the networks. An embedded representation is generated using the trained network embedding model to represent an input network, with associated attribute information, in a network topology space. A machine learning task is performed using the embedded representation as input to a machine learning model.

Provided herein are detection systems and related methods for detecting moving objects in an airspace surrounding the detection system. In an aspect, the moving object is a flying animal and the detection system comprises a first imager and a second imager that determines position of the moving object and for moving objects within a user selected distance from the system the system determines whether the moving object is a flying animal, such as a bird or bat. The systems and methods are compatible with wind turbines to identify avian(s) of interest in airspace around wind turbines and, if necessary, take action to minimize avian strike by a wind turbine blade.

A method may include training a machine learning model to perform a first task before training the machine learning model to perform the second task. The machine learning model includes a generator network and a discriminator network. The training includes training, based on a first training sample associated with the first task, the discriminator network to perform the first task. The generator network may be trained to generate a first synthetic training sample emulating the first training sample. The discriminator network trained to perform the first task may be reinitialized in order for the discriminator network to be trained, based on a second training sample, to perform the second task. The reinitialized discriminator network may be further retrained, based on the first synthetic training sample, to perform the first task. Related systems and articles of manufacture, including computer program products, are also provided.

A facial verification method includes separating a query face image into color channel images of different color channels, obtaining a multi-color channel target face image with a reduced shading of the query face image based on a smoothed image and a gradient image of each of the color channel images, extracting a face feature from the multi-color channel target face image, and determining whether face verification is successful based on the extracted face feature.

Systems and methods change a user interface for the purpose of guiding a user in supplementing a product listing with an image to evidence the product's authenticity. Example embodiments include a machine-implemented method for accessing at least one database to retrieve an authenticity criterion mapped to a product and at least one reference image that depicts adequate detail of a product specimen to fulfill the authenticity criterion. The machine can further cause a user device to display the reference image to the user along with a suggestion that the user submit a candidate image depicting similar detail of the product. In some example embodiments, the method further includes retrieving the candidate image, confirming receipt of the candidate image, and displaying the candidate image, as well as adjusting a rank for a candidate specimen based on various factors.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for content presentation. In one aspect, a method includes receiving a request for a content item to be presented to a user; for a collection of content items, identifying one or more candidate content items including using image keywords derived from images associated with the user to identify the one or more candidate content items; selecting a content item responsive to the content request from the candidate content items; and sending the selected content item for presentation to the user.

A client device configured with a neural network includes a processor, a memory, a user interface, a communications interface, a power supply and an input device, wherein the memory includes a trained neural network received from a server system that has trained and configured the neural network for the client device. A server system and a method of training a neural network are disclosed.

An imaging system for creating an image of a target object comprising a mirror mounted on a gimbal and arranged to rotate about at least one axis, a gimbal drive unit configured to control the orientation of the gimbal, and a camera having its optical axis directed onto the mirror in order that an image reflected in the mirror is within a field of view of the camera, wherein the control unit is arranged to position the gimbal such that a reflection of a target object is within a field of view of the camera.