Methods and systems for aligning images of a specimen generated with different modes of an imaging subsystem are provided. One method includes separately aligning first and second images generated with first and second modes, respectively, to a design for the specimen. For a location of interest in the first image, the method includes generating a first difference image for the location of interest and the first mode and generating a second difference image for the location of interest and the second mode. The method also includes aligning the first and second difference images to each other and determining information for the location of interest from results of the aligning.

An image forming apparatus includes a display device, a first detection unit, a second detection unit, a first acquisition unit, and an output unit. The display device displays at least one image for display. The first detection unit detects a user's selection of an image for display in at least one image for display. The second detection unit detects an input to a drawing region of drawing indicating an image quality abnormality with respect to a target image corresponding to the selected image for display. The first acquisition unit acquires drawing information based on the input of the drawing detected by the second detection unit. The output unit outputs the drawing information acquired by the first acquisition unit.

An image forming apparatus includes a display device, a first detection unit, a second detection unit, a first acquisition unit, and an output unit. The display device displays at least one image for display. The first detection unit detects a user's selection of an image for display in at least one image for display. The second detection unit detects an input to a drawing region of drawing indicating an image quality abnormality with respect to a target image corresponding to the selected image for display. The first acquisition unit acquires drawing information based on the input of the drawing detected by the second detection unit. The output unit outputs the drawing information acquired by the first acquisition unit.

Embodiments described herein provide systems and processes for scene-aware object detection. This can involve an object detector that modulates its operations based on image location. The object detector can be a neural network detector or a scanning window detector, for example.

Embodiments described herein provide systems and processes for scene-aware object detection. This can involve an object detector that modulates its operations based on image location. The object detector can be a neural network detector or a scanning window detector, for example.

A device, method and system for estimating elevation in images from camera devices is provided. The device detects humans at respective positions in images from a camera device, the camera device having a fixed orientation and fixed focal length. The device estimates, for the humans in the images, respective elevations of the humans, relative to the camera device, at the respective positions based at least on camera device parameters defining the fixed orientation and the fixed focal length. The device associates the respective elevations with the respective positions in the images. The device determines, using the respective elevations associated with the respective positions, a function that estimates elevation in an image from the camera device, using a respective image position coordinate as an input. The device provides the function to a video analytics engine to determine relative real-world positions in subsequent images from the camera device.

A method and a device for determining a placement region of an item are disclosed. The method according to the present disclosure comprises: acquiring position information of an electronic identification at a bar display screen; and determining the placement region of the item according to the position information and a preset mapping relationship.

A method and a device for determining a placement region of an item are disclosed. The method according to the present disclosure comprises: acquiring position information of an electronic identification at a bar display screen; and determining the placement region of the item according to the position information and a preset mapping relationship.

The present application related to a method for detecting an object image using a convolutional neural network. Firstly, obtaining feature images by Convolution kernel, and then positioning an image of an object under detected by a default box and a boundary box from the feature image. By Comparing with the sample image, the detected object image is classifying to an esophageal cancer image or a non-esophageal cancer image. Thus, detecting an input image from the image capturing device by the convolutional neural network to judge if the input image is the esophageal cancer image for helping the doctor to interpret the detected object image.

Disclosed is a system and method for obtaining optical properties of skin on a human face through face video analysis. Video of the face is captured, landmarks on the face and tracked, regions-of-interest are defined and tracked using the landmarks, some measurements/optical properties are obtained, the time-based video is transformed into an angular domain, and additional measurements/optical properties are obtained. Such optical properties can be measured using video in real-time or video that has been pre-recorded.