Abstract: A method for generating packing solution of printed circuit board (PCB) comprises: obtaining a plurality of component files, a first constraint, and a second constraint, wherein each of the component files corresponds to an electrical component, the first constraint corresponds to a signal-PCB, and the second constraint corresponds to a multiple-PCB; performing a genetic algorithm according to the plurality of component files and the first constraint files to generate a plurality of single-PCB feasible solutions, wherein each of the plurality of single-PCB feasible solutions has a shape description, performing a concave hull algorithm to update the shape description according to each of the plurality of single-PCB feasible solutions, after updating the shape description, performing the genetic algorithm according to the plurality of single-PCB feasible solutions and the second constraint to generate a multiple-PCB packing solution.

Abstract: A human resource management method, comprising: obtaining a feature parameter associated with an employee; performing a prediction algorithm based on machine learning according to the feature parameter to output a human resource index; and performing a classification procedure to convert the human resource index to an understandable information.

Abstract: A product order prediction method adapts to a production planning system. The method comprises obtaining a reference data related to a next reference order and a current actual order, performing an algorithm based on the neural network model according to the reference data and the current actual order to generate a feature vector, and performing another algorithm based on the neural network model according to the feature vector to output a next predicted order to the production planning system, for the production planning system to generate an operation plan of a production line of the product according to the next predicted order.

Abstract: A surface defect detection method applied to a surface of an object is disclosed. The method includes obtaining an image of the surface, performing a deep learning algorithm by a computing device to set a plurality of bounding boxes in the image and to output a plurality of feature parameter sets associated with the plurality of bounding boxes, with each bounding box enclosing a possible defect of the surface, and performing a classifying algorithm by the computing device according to the bounding boxes and the feature parameters to determine whether the surface conforms to a specification.

Abstract: Examples provided relate to adding a network unit to a management group. An example method includes receiving a numeric code on a first network unit from a button on a front panel of the first network unit. The numeric code is received on a second network unit using a button on a front panel of the second network unit. The first network unit is added to the management group of the second network unit.

Abstract: Examples provided relate to adding a network unit to a management group. An example method includes receiving a numeric code on a first network unit from a button on a front panel of the first network unit. The numeric code is received on a second network unit using a button on a front panel of the second network unit. The first network unit is added to the management group of the second network unit.

Abstract: An apparatus, method and computer program product for presenting burst images are provided. The apparatus may include a processor that may be configured to receive a plurality of burst images. Each burst image may differ from the other burst images based on a variable parameter. The processor may also be configured to provide for a presentation of a sample burst image. In this regard, the sample burst image may be one of the plurality of burst images. The processor may be further configured to receive a selected location within the presentation of the sample burst image and provide for a presentation of a plurality of burst image fragments associated with each of the plurality of burst images. In this regard, the burst image fragments may be portions of each of the burst images, where the areas of each burst image may be determined based on the selected location.

Abstract: A method for object tracking is provided. The method may include identifying a first interest point, receiving a video frame, and detecting, via a processor, a second interest point in the video frame using a scale space image pyramid. The method may further include matching the second interest point with the first interest point, and determining a motion estimation based on the matched interest points. Similar apparatuses and computer program products are also provided.

Abstract: An apparatus includes means for associating a first editing effect with a first editing direction; means for associating a second editing effect with a second editing direction; means for receiving an editing input indicating an input direction and an input length; means for determining an editing degree according to a corresponding length of said input length in an editing direction by extracting a component corresponding to the input in the editing direction; and means for applying said associated editing effect in a degree according to the editing degree to an image.

Abstract: A method for providing image modification may include searching an image gallery based on a characteristic of a captured image, determining a correlation between the captured image and a similar image from the image gallery, the similar image sharing the characteristic, and enabling modification of the captured image based on features associated with the similar image that are not visible in the captured image. An apparatus and computer program product corresponding to the method are also provided.

Abstract: An apparatus, method and computer program product for presenting burst images are provided. The apparatus may include a processor that may be configured to receive a plurality of burst images. Each burst image may differ from the other burst images based on a variable parameter. The processor may also be configured to provide for a presentation of a sample burst image. In this regard, the sample burst image may be one of the plurality of burst images. The processor may be further configured to receive a selected location within the presentation of the sample burst image and provide for a presentation of a plurality of burst image fragments associated with each of the plurality of burst images. In this regard, the burst image fragments may be portions of each of the burst images, where the areas of each burst image may be determined based on the selected location.

Abstract: A method for processing texture mapping by biasing level of detail (LOD) according to image content includes: a texture request for fetching a target texel is received. The texture request includes a target texture coordinate at a target LOD of a target texture mipmap corresponding to the target texel. A target level of content (LOC) bias map corresponding to the target texture mipmap is looked up according to the target texture coordinate and the target LOD to fetch a target LOC bias value corresponding to the target texture coordinate at the target LOD. A replacement LOD is calculated according to the target LOD and the target LOC bias value. A replacement texel is fetched at a corresponding coordinate, which corresponds to the target texture coordinate, at the replacement LOD of the target texture mipmap. Texture filtering is processed according to the replacement texel.

Abstract: An apparatus for presenting burst images is provided. The apparatus may include a processor that may be configured to receive a plurality of burst images. Each burst image may differ from the other burst images based on a variable parameter, such as, but not limited to, exposure, focus, and/or time, or to the state of a target, such as the varying facial expression of a person. The processor may also be configured to provide for a presentation of a sample burst image. In this regard, the sample burst image may be one of the plurality of burst images. The processor may be further configured to receive a selected location within the presentation of the sample burst image and provide for a presentation of a plurality of burst image fragments associated with each of the plurality of burst images. In this regard, the burst image fragments may be portions of each of the burst images, where the areas of each burst image may be determined based on the selected location.

Abstract: An apparatus includes means for receiving input indicating a selection point; generating a set of paths originating from said selection point; determining an influence value for each point on a path to generate an influence map; and applying said influence map to an image.

Abstract: An apparatus includes means for associating a first editing effect with a first editing direction; means for associating a second editing effect with a second editing direction; means for receiving an editing input indicating an input direction and an input length; means for determining an editing degree according to a corresponding length of said input length in an editing direction by extracting a component corresponding to the input in the editing direction; and means for applying said associated editing effect in a degree according to the editing degree to an image.

Abstract: The present invention discloses an auxiliary steering system, which is installed in the steering wheel of a vehicle. In the present invention, a gear-operation device is installed in the steering wheel; a dynamic device is installed in steering column of the steering wheel and utilizes a transmission device to drive the gear-operation device; and a controller is connected to the dynamic device and controls the dynamic device to operate the steering wheel. The present invention enables a common vehicle to achieve automatic driving without changing the original vehicle structure. Further, the assistant mechanism of the present invention makes manual driving easier, and the safety mechanism of the present invention makes automatic driving safer.

Abstract: A method for object tracking is provided. The method may include identifying a first interest point, receiving a video frame, and detecting, via a processor, a second interest point in the video frame using a scale space image pyramid. The method may further include matching the second interest point with the first interest point, and determining a motion estimation based on the matched interest points. Similar apparatuses and computer program products are also provided.

Abstract: Methods and systems for texture mapping in a computer-implemented graphics pipeline are described. A sample group is identified as including a divergent pixel. A determination is made whether an operand of an instruction executing on the divergent pixel satisfies a condition. A scheme for determining a level of detail for the texture mapping is selected depending on whether or not the condition is satisfied.

Abstract: A method for providing image modification may include searching an image gallery based on a characteristic of a captured image, determining a correlation between the captured image and a similar image from the image gallery, the similar image sharing the characteristic, and enabling modification of the captured image based on features associated with the similar image that are not visible in the captured image. An apparatus and computer program product corresponding to the method are also provided.

Abstract: An apparatus for presenting burst images is provided. The apparatus may include a processor that may be configured to receive a plurality of burst images. Each burst image may differ from the other burst images based on a variable parameter, such as, but not limited to, exposure, focus, and/or time, or to the state of a target, such as the varying facial expression of a person. The processor may also be configured to provide for a presentation of a sample burst image. In this regard, the sample burst image may be one of the plurality of burst images. The processor may be further configured to receive a selected location within the presentation of the sample burst image and provide for a presentation of a plurality of burst image fragments associated with each of the plurality of burst images. In this regard, the burst image fragments may be portions of each of the burst images, where the areas of each burst image may be determined based on the selected location.