A method for parallel processing a digitally scanned pathology image is performed by a plurality of processors and includes performing, by a first processor, a first operation of generating a first batch from a first set of patches extracted from a digitally scanned pathology image and providing the generated first batch to a second processor, performing, by the first processor, a second operation of generating a second batch from a second set of patches extracted from the digitally scanned pathology image and providing the generated second batch to the second processor, and performing, by the second processor, a third operation of outputting a first analysis result from the first batch by using a machine learning model, with at least part of time frame for the second operation performed by the first processor overlapping at least part of time frame for the third operation performed by the second processor.

An apparatus and a method with image recognition-based security are disclosed. The method includes, for an unlocked terminal, tracking a face detected in a previous frame, detecting a background region change between the previous frame and a current frame based on a region of the tracked face, when the background region change is not detected, determining whether a state maintenance time fails to meet a preset time, in response to the state maintenance time failing to meet the preset time, determining an operation mode to be a first operation mode for determining whether recognition succeeds for the current frame, performing the first operation mode, including performing face detection with respect to the current frame, and maintaining the unlocked state of the terminal for the current frame when the face is detected as a result of the performing of the face detection, representing that the recognition succeeded for the current frame.

An apparatus and a method with image recognition-based security are disclosed. The method includes, for an unlocked terminal, tracking a face detected in a previous frame, detecting a background region change between the previous frame and a current frame based on a region of the tracked face, when the background region change is not detected, determining whether a state maintenance time fails to meet a preset time, in response to the state maintenance time failing to meet the preset time, determining an operation mode to be a first operation mode for determining whether recognition succeeds for the current frame, performing the first operation mode, including performing face detection with respect to the current frame, and maintaining the unlocked state of the terminal for the current frame when the face is detected as a result of the performing of the face detection, representing that the recognition succeeded for the current frame.

An information processing apparatus includes a processor configured to: acquire a captured image of an object; specify a first area of the object in the captured image, the first area being an area occupied by a work target that is a target to be worked on; process the captured image to make a second area other than the first area invisible to generate a processed image; in response to a change in the first area with a deformation of the work target, apply a deformation area instead of the first area to make a second area obtained by the application invisible to generate a processed image, the deformation area being an area defined by a pre-registered shape of the work target after deformation; and transmit the processed image.

An information processing apparatus includes a processor configured to: acquire a captured image of an object; specify a first area of the object in the captured image, the first area being an area occupied by a work target that is a target to be worked on; process the captured image to make a second area other than the first area invisible to generate a processed image; in response to a change in the first area with a deformation of the work target, apply a deformation area instead of the first area to make a second area obtained by the application invisible to generate a processed image, the deformation area being an area defined by a pre-registered shape of the work target after deformation; and transmit the processed image.

A high efficiency method of processing images to provide perceptual high-contrast output. Pixel intensities are calculated by a weighted combination of a fixed number of static bounding rectangle sizes. This is more performant than incrementally growing the bounding rectangle size and performing expensive analysis on resultant histograms. To mitigate image artifacts and noise, blurring and down-sampling are applied to the image prior to processing.

The present invention provides a shaft rotational speed measurement device and method based on variable density sinusoidal fringe pattern. The device comprises a variable density sinusoidal fringe pattern sensor, a high speed image acquisition and transmission module, a computer, and an image processing software module. The method comprises the following steps: make the variable density sinusoidal fringe pattern sensor attached on the circumferential surface of the measured shaft, the variable density sinusoidal fringe pattern sensor is continuously imaged and recorded by the high speed image acquisition module, the image transmission module transfers the fringe pattern signal to the computer, the image processing software module carries out Fourier transform to the fringe pattern signal in the same position of each frame, and corrects the peak frequency accurately by using the peak frequency correction method to obtain the accurate fringe pattern density information of each frame, obtains the time domain curve of the rotational angular velocity of the measured shaft, and then calculate the rotational speed of the measured shaft through the rotational angular velocity and sampling frequency. The present invention can realize non-contact measurement of rotational speed of measured shaft within a certain speed range, and the measuring device is simple, the measuring method is fast and accurate.

An image processing apparatus, includes a memory; and a processor coupled to the memory and configured to: generate a trained machine learning model by learning a machine learning model using a first set of image data, output an inference result by inputting a second set of image data to the trained machine learning model, and process a region of interest at a time of inference with respect to image data for which an inference result is correct in the second set of image data.

Systems and methods for eye image set selection, eye image collection, and eye image combination are described. Embodiments of the systems and methods for eye image set selection can include comparing a determined image quality metric with an image quality threshold to identify an eye image passing an image quality threshold, and selecting, from a plurality of eye images, a set of eye images that passes the image quality threshold.

An information processing apparatus (10) is for supporting work by a user who uses drawings for a plant. The information processing apparatus (10) includes a controller (15). The controller (15) is configured to convert a drawing including elements configuring the plant into an abstract model represented by element information indicating the elements and connection information indicating a connection relationship between the elements. The controller (15) is configured to generate display information, when it is judged that a difference exists between one abstract model based on one drawing and another abstract model based on another drawing, for displaying the differing portion in a different form than another portion.