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382 results about "Design characteristics" patented technology

Design characteristics / characteristic. Those dimensional, visual, functional, mechanical, and material features or properties, which describe and constitute the design of the article, as specified by drawing or DPD requirements.

Thin hollow backlights with beneficial design characteristics

InactiveUS20100156953A1Reduce the total massLosses associated with the light sources are kept to minimal levelsCathode-ray tube indicatorsHollow light guidesBack reflectorLight guide
A backlight unit (10) has a hollow cavity (16) instead of employing a light guide. One or more light sources (24a-c), such as LEDs, are arranged to emit light into the cavity, which is formed by a front (12) and a back reflector (14). The backlight is typically of the edge-lit type. The backlight can have a large area, is thin and consists of fewer components than conventional devices. Its design permits light recycling. The unit emits light of a predefined polarisation and can be arranged to have desired horizontal/vertical viewing angle properties. Light is uniformly distributed within the guide and the light output (20b, 2Od) is substantially collimated. Such backlights occupy a specific region in a parameter space defined by two parameters: first, the ratio of the output emission area to the total source emission area should lie in the range 0.0001 to 0.1; and second, the ratio of the SEP to the height of the cavity (H) should be in the range 3 to 10, where the SEP is an average plan view source separation, a special measure of the average spacing of light sources in the plane of the unit. There is also a discussion on the required number of light sources N, their arrangement near the periphery of the cavity, as well as the shape and size of the output emission area. A required minimum brightness uniformity (VESA) value to be maintained, when a subset of Madjacent sources is switched off (where M is at least 0.1 N or M>2 or both), is also disclosed. The backlight can be used for a display or for general lighting purposes.
Owner:3M INNOVATIVE PROPERTIES CO

Infrared behavior identification method based on adaptive fusion of artificial design feature and depth learning feature

The invention relates to an infrared behavior identification method based on adaptive fusion of an artificial design feature and a depth learning feature. The method comprises: S1, improved dense track feature extraction is carried out on an original video by using an artificial design feature module; S2, feature coding is carried out on the extracted artificial design feature; S3, with a CNN feature module, optic flow information extraction is carried out on an original video image sequence by using a variation optic flow algorithm, thereby obtaining a corresponding optic flow image sequence; S4, CNN feature extraction is carried out on the optic flow sequence obtained at the S3 by using a convolutional neural network; and S5, a data set is divided into a training set and a testing set; and weight learning is carried out on the training set data by using a weight optimization network, weight fusion is carried out on probability outputs of a CNN feature classification network and an artificial design feature classification network by using the learned weight, an optimal weight is obtained based on a comparison identification result, and then the optimal weight is applied to testing set data classification. According to the method, a novel feature fusion way is provided; and reliability of behavior identification in an infrared video is improved. Therefore, the method has the great significance in a follow-up video analysis.
Owner:CHONGQING UNIV OF POSTS & TELECOMM

Fast high-resolution SAR (synthetic aperture radar) image ship detection method based on feature fusion and clustering

The invention discloses a fast high-resolution SAR (synthetic aperture radar) image ship detection method based on feature fusion and clustering. The fast high-resolution SAR image ship detection method comprises the following steps: on the basis of the back scattering characteristics of each ground object and the prior information of a ship target in an SAR image, positioning a target potential position index map by an Otsu algorithm and range constraint; on the index map, pre-screening to obtain a detection binary segmentation map by a CFAR (constant false alarm rate) algorithm based on a local contrast; carrying out morphological processing to a detection result, and extracting a potential target slice from the SAR image and a detected binary segmentation map according to a processing result; and carrying out K-means clustering to the extracted slice by a designed identification feature to obtain a final identification result. According to the fast high-resolution SAR image ship detection method based on feature fusion and clustering, the data volume of a detection stage is effectively reduced by pre-processing, and point-to-point detection is not needed/the time of point-to-point detection is saved. Meanwhile, a target identification problem under the condition of insufficient training samples at present can be solved by the designed characteristic and a non-supervision clustering method, the target can be effectively positioned, and the size of the target can be estimated.
Owner:西安维恩智联数据科技有限公司
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