A client device receives a first map tile, a second map tile, and map terrain data from a mapping system, the first and second map tiles together including map feature having a geometric base with a height value, the geometric base represented by a set of vertices split across the first and second map tiles. The client device identifies edges of the geometric base that intersect a tile border between the first and second map tiles. The client device determines a set of sample points based on the identified edges and determines a particular sample elevation value corresponding to a sample point in the set. The client device renders the map feature based on the particular sample elevation value and displays the rendering of the map feature.

Described are systems and method directed to generation of a dimensionally accurate three-dimensional (“3D”) body model of a body, such as a human body, based on two-dimensional (“2D”) images of that body. A user may use a 2D camera, such as a digital camera typically included in many of today's portable devices (e.g., cell phones, tablets, laptops, etc.) and obtain a series of 2D body images of their body from different directions with respect to the camera. The 2D body images may then be used to generate a plurality of predicted body parameters corresponding to the body represented in the 2D body images. Those predicted body parameters may then be further processed to generate a dimensionally accurate 3D model of the body of the user.

Described are systems and method directed to generation of a dimensionally accurate three-dimensional (“3D”) body model of a body, such as a human body, based on two-dimensional (“2D”) images of that body. A user may use a 2D camera, such as a digital camera typically included in many of today's portable devices (e.g., cell phones, tablets, laptops, etc.) and obtain a series of 2D body images of their body from different directions with respect to the camera. The 2D body images may then be used to generate a plurality of predicted body parameters corresponding to the body represented in the 2D body images. Those predicted body parameters may then be further processed to generate a dimensionally accurate 3D model of the body of the user.

Methods and systems for determining a plurality of sequences of nucleic acid (e.g., DNA) molecules in a sequencing-by-synthesis process are provided. In one embodiment, the method comprises obtaining images of fluorescent signals obtained in a plurality of synthesis cycles. The images of fluorescent signals are associated with a plurality of different fluorescence channels. The method further comprises preprocessing the images of fluorescent signals to obtain processed images. Based on a set of the processed images, the method further comprises detecting center positions of clusters of the fluorescent signals using a trained convolutional neural network (CNN) and extracting, based on the center positions of the clusters of fluorescent signals, features from the set of the processed images to generate feature embedding vectors. The method further comprises determining, in parallel, the plurality of sequences of DNA molecules using the extracted features based on a trained attention-based neural network.

Methods and systems for determining a plurality of sequences of nucleic acid (e.g., DNA) molecules in a sequencing-by-synthesis process are provided. In one embodiment, the method comprises obtaining images of fluorescent signals obtained in a plurality of synthesis cycles. The images of fluorescent signals are associated with a plurality of different fluorescence channels. The method further comprises preprocessing the images of fluorescent signals to obtain processed images. Based on a set of the processed images, the method further comprises detecting center positions of clusters of the fluorescent signals using a trained convolutional neural network (CNN) and extracting, based on the center positions of the clusters of fluorescent signals, features from the set of the processed images to generate feature embedding vectors. The method further comprises determining, in parallel, the plurality of sequences of DNA molecules using the extracted features based on a trained attention-based neural network.

A method and apparatus for waking up a device, an electronic device, and a storage medium are provided, which are related to fields of image processing and deep learning. The method includes: acquiring an environment image of a surrounding environment of a target device in real time, and recognizing a face region of a user in the environment image; acquiring a plurality of facial landmarks in the face region, and acquiring a left eye image and a right eye image according to the facial landmarks; acquiring a left eye sight classification result and a right eye sight classification result according to the left eye image and the right eye image; and waking up the target device in a case of determining that the user is looking at the target device according to the left eye sight classification result and the right eye sight classification result.

A method and apparatus for waking up a device, an electronic device, and a storage medium are provided, which are related to fields of image processing and deep learning. The method includes: acquiring an environment image of a surrounding environment of a target device in real time, and recognizing a face region of a user in the environment image; acquiring a plurality of facial landmarks in the face region, and acquiring a left eye image and a right eye image according to the facial landmarks; acquiring a left eye sight classification result and a right eye sight classification result according to the left eye image and the right eye image; and waking up the target device in a case of determining that the user is looking at the target device according to the left eye sight classification result and the right eye sight classification result.

An information processing device includes a picture image inputter configured to acquire a picture image imaged by a camera and at least one processor configured to execute a program stored in a memory. The at least one processor detects, from the picture image acquired by the picture image inputter, light emitted by a light-emission device, acquires, based on brightness of the detected light emitted by the light-emission device, set brightness information indicating an appropriate brightness for light to be emitted by the light-emission device, and transmits the acquired set brightness information to the light-emission device.

An information processing device includes a picture image inputter configured to acquire a picture image imaged by a camera and at least one processor configured to execute a program stored in a memory. The at least one processor detects, from the picture image acquired by the picture image inputter, light emitted by a light-emission device, acquires, based on brightness of the detected light emitted by the light-emission device, set brightness information indicating an appropriate brightness for light to be emitted by the light-emission device, and transmits the acquired set brightness information to the light-emission device.

A localization method and system for mobile remote inspection and/or manipulation tools in confined spaces are provided. The system comprises a mobile remote inspection and/or manipulation device including a carrier movable within the confined space and an inspection and/or manipulation tool, such as an inspection camera, pose sensors arranged on the movable carrier for providing signals indicative of the position and orientation of the movable carrier, and distance sensors arranged on the movable carrier for providing signals indicative of the distance to interior surfaces of the confined space. The localization method makes use of probalistic sensor fusion of the measurement data provided by the pose sensors and the distance sensors in order to precisely determine the actual pose of the movable carrier and localize data generated by the inspection and/or manipulation tool.