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公开(公告)号:US11922708B2
公开(公告)日:2024-03-05
申请号:US17942898
申请日:2022-09-12
申请人: UATC, LLC
IPC分类号: G06K9/00 , G06F18/214 , G06F18/241 , G06F18/243 , G06N7/01 , G06N20/00 , G06T7/521 , G06T15/08 , G06V10/28 , G06V10/50 , G06V10/56 , G06V10/764 , G06V20/58 , G06V20/64 , G05D1/00
CPC分类号: G06V20/64 , G06F18/214 , G06F18/241 , G06F18/24323 , G06N7/01 , G06N20/00 , G06T7/521 , G06T15/08 , G06V10/28 , G06V10/50 , G06V10/56 , G06V10/764 , G06V20/58 , G06V20/584 , G05D1/0238 , G05D2201/0213 , G06T2207/20081 , G06T2207/30261 , G06T2210/12
摘要: Systems, methods, tangible non-transitory computer-readable media, and devices for autonomous vehicle operation are provided. For example, a computing system can receive object data that includes portions of sensor data. The computing system can determine, in a first stage of a multiple stage classification using hardware components, one or more first stage characteristics of the portions of sensor data based on a first machine-learned model. In a second stage of the multiple stage classification, the computing system can determine second stage characteristics of the portions of sensor data based on a second machine-learned model. The computing system can generate an object output based on the first stage characteristics and the second stage characteristics. The object output can include indications associated with detection of objects in the portions of sensor data.
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42.
公开(公告)号:US20240071070A1
公开(公告)日:2024-02-29
申请号:US18270649
申请日:2021-12-30
发明人: Ook Sang YOO , Ji Yea CHON , Hyuk Jae LEE , Kyeong Jong LIM
IPC分类号: G06V10/70 , G06V10/28 , G06V10/764 , G06V10/82 , G06V20/70
CPC分类号: G06V10/87 , G06V10/28 , G06V10/764 , G06V10/82 , G06V20/70
摘要: Provided is an image recognition method including the steps of: for a deep learning network that carries out object recognition on a random image, carrying out quantization corresponding to the number of a plurality of different bits to generate a plurality of quantization models respectively corresponding to the number of bits; receiving image data as an input for the deep learning network; determining the uncertainty of the input image data; selecting any one of the plurality of quantization models on the basis of the determined uncertainty; and recognizing an object from the image data by using the selected quantization model, and outputting, as the result of the object recognition, a label corresponding to the image data.
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公开(公告)号:US11915498B2
公开(公告)日:2024-02-27
申请号:US17688063
申请日:2022-03-07
发明人: Toshikazu Taki
CPC分类号: G06V20/62 , G06T7/49 , G06V10/28 , G06V10/454 , G06V10/457 , G06V10/751 , G06V10/82 , G06V2201/02
摘要: According to one embodiment, a reading system includes an extractor, a determiner, and a reader. The extractor extracts a candidate image from an input image. The candidate image is of a portion of the input image in which a segment display is imaged. The determiner calculates an angle with respect to a reference line of each of a plurality of straight lines detected from the candidate image, and determines whether or not the candidate image is an image of a segment display based on a distribution indicating a relationship between the angle and a number of the straight lines. The reader reads a numerical value displayed in a segment display from the candidate image determined to be an image of a segment display.
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44.
公开(公告)号:US11915410B2
公开(公告)日:2024-02-27
申请号:US18138501
申请日:2023-04-24
发明人: Lu Li , Zhiyu Wang , Guannan Jiang
CPC分类号: G06T7/0008 , G06T3/60 , G06T5/20 , G06T7/13 , G06V10/25 , G06V10/28 , G06V10/751 , G06V10/761 , G06T2207/20164
摘要: A method and an apparatus for inspecting tab appearance of cell assembly, an electronic device, a non-transitory computer-readable storage medium, and a computer program product are provided. The method includes: obtaining an image for inspection that includes a background region and a cell assembly image region, where the cell assembly image region includes a body zone and a plurality of tab stacking regions, each tab stacking region adjoining a top edge or a bottom edge of the body zone; determining each root corner of the plurality of tab stacking regions in the image for inspection; determining two side edges of the body zone in the image for inspection; determining at least one reference edge line in the image for inspection based on the two side edges of the body zone in the image for inspection; and determining result information of the tab appearance inspection based on each root corner of the plurality of tab stacking regions in the image for inspection and the at least one reference edge line.
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公开(公告)号:US20240046605A1
公开(公告)日:2024-02-08
申请号:US17817954
申请日:2022-08-05
申请人: Motional AD LLC
摘要: Systems and methods are disclosed for identifying visibility of a physical space using visibility values and indications of uncertainty associated with the visibility values. One method can include capturing an image of a physical space, dividing pixels of the image into presumably well-lit and presumably not well-lit categories based on an intensity threshold, generating an evidential illumination map for the image based at least partly on a comparison between a value of each pixel to the intensity threshold, and projecting the evidential illumination map onto data representing a three-dimensional scan of the physical space. Evidential values can enable an autonomous vehicle to more safely navigate spaces using camera data by enabling programmatic determination of uncertainty for the camera data.
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公开(公告)号:US20240037745A1
公开(公告)日:2024-02-01
申请号:US18172706
申请日:2023-02-22
发明人: Guan-Yu Chen , Ren-Hao Xie , Shiue-Luen Chen
CPC分类号: G06T7/0014 , G06V10/28 , G06V10/25 , G06V10/457 , G06T2207/10016 , G06T2207/30061 , G06V2201/07
摘要: A method of tracking movement of particles in bronchus includes obtaining, from a video of the particles, a plurality of processed images, each of which contains a plurality of particle portions representing the particles, and implementing a tracking process for a reference image of the processed images. The tracking process includes, for each particle portion in the reference image, selecting a to-be-compared portion from among the particle portions in a next image immediately following the reference image, obtaining an expected range of movement of the particle represented by the particle portion according to a position of the particle portion, determining whether a corresponding position in the reference image that corresponds to a position of the to-be-compared portion in the next image is within the expected range, and storing the position of the to-be-compared portion into a track record that is associated with the particle when the determination is affirmative.
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47.
公开(公告)号:US20240029233A1
公开(公告)日:2024-01-25
申请号:US18138501
申请日:2023-04-24
发明人: Lu LI , Zhiyu WANG , Guannan JIANG
CPC分类号: G06T7/0008 , G06T3/60 , G06T5/20 , G06T7/13 , G06V10/25 , G06V10/28 , G06V10/751 , G06V10/761 , G06T2207/20164
摘要: A method and an apparatus for inspecting tab appearance of cell assembly, an electronic device, a non-transitory computer-readable storage medium, and a computer program product are provided. The method includes: obtaining an image for inspection that includes a background region and a cell assembly image region, where the cell assembly image region includes a body zone and a plurality of tab stacking regions, each tab stacking region adjoining a top edge or a bottom edge of the body zone; determining each root corner of the plurality of tab stacking regions in the image for inspection; determining two side edges of the body zone in the image for inspection; determining at least one reference edge line in the image for inspection based on the two side edges of the body zone in the image for inspection; and determining result information of the tab appearance inspection based on each root corner of the plurality of tab stacking regions in the image for inspection and the at least one reference edge line.
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公开(公告)号:US20230410314A1
公开(公告)日:2023-12-21
申请号:US18241179
申请日:2023-08-31
申请人: Snap Inc.
发明人: Fedir POLIAKOV
IPC分类号: G06T7/11 , G06T7/62 , G06T7/66 , G06T7/73 , G06T7/136 , G06V10/28 , G06V10/20 , G06V40/19 , G06V40/16 , G06V40/18 , G06T7/90
CPC分类号: G06T7/11 , G06T7/62 , G06T7/66 , G06T7/73 , G06T7/136 , G06V10/28 , G06V10/255 , G06V40/19 , G06V40/162 , G06V40/193 , G06V40/197 , G06T7/90 , G06T2207/10024 , G06T2207/30041
摘要: Systems, devices, media, and methods are presented for gaze-based control of device operations. One method includes receiving a video stream from an imaging device, the video stream depicting one or more eyes, determining a gaze direction for the one or more eyes depicted in the video stream, detecting a change in the gaze direction of the one or more eyes, and triggering an operation in a client device based on the change in the gaze direction.
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49.
公开(公告)号:US20230401738A1
公开(公告)日:2023-12-14
申请号:US18237937
申请日:2023-08-25
发明人: Shingo MINE
CPC分类号: G06T7/70 , G06T15/00 , G06T7/50 , G06V10/28 , G06V10/761 , G06V2201/07 , G06T2207/10024 , G06T2207/20101
摘要: An image processing device includes an object detecting unit that processes captured image data representing a captured image, which is an image including an object or detection target and a background of the object, to generate processed image data representing a processed image, which is an image in which the object is detected; an expected-data generating unit that generates expected data representing an expected image, which a virtual image in which the object represented by an attribute is placed at a position on the background on the basis of object data representing the position of the object and background data representing the background; and a detection-result determining unit that compares the processed image data and the expected data to determine whether or not the object is detected correctly in the processed image data.
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公开(公告)号:US20230386068A1
公开(公告)日:2023-11-30
申请号:US18134366
申请日:2023-04-13
申请人: SICK AG
发明人: Romain MÜLLER , Pascal SCHÜLER
CPC分类号: G06T7/62 , G06K7/1456 , G06T5/40 , G06T7/11 , G06V10/28 , G06V10/761 , G06T2207/20084
摘要: A method of determining the module size of an optical code (20) is specified in which image data having the code (20) are recorded and the module size is estimated from distances between light-dark transitions in the image data, At least one frequency distribution, in particular a histogram, is formed that indicates how often dark and/or light pixel sequences of a respective number occur along at least one line through the code (20) and the module size is estimated from the frequency distribution.
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