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公开(公告)号:US11315021B2
公开(公告)日:2022-04-26
申请号:US16259389
申请日:2019-01-28
申请人: Stradvision, Inc.
发明人: Kye-Hyeon Kim , Yongjoong Kim , Insu Kim , Hak-Kyoung Kim , Woonhyun Nam , SukHoon Boo , Myungchul Sung , Donghun Yeo , Wooju Ryu , Taewoong Jang , Kyungjoong Jeong , Hongmo Je , Hojin Cho
摘要: A method for on-device continual learning of a neural network which analyzes input data is provided to be used for smartphones, drones, vessels, or a military purpose. The method includes steps of: a learning device, (a) sampling new data to have a preset first volume, instructing an original data generator network, which has been learned, to repeat outputting synthetic previous data corresponding to a k-dimension random vector and previous data having been used for learning the original data generator network, such that the synthetic previous data has a second volume, and generating a batch for a current-learning; and (b) instructing the neural network to generate output information corresponding to the batch. The method can be performed by generative adversarial networks (GANs), online learning, and the like. Also, the present disclosure has effects of saving resources such as storage, preventing catastrophic forgetting, and securing privacy.
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公开(公告)号:US11010668B2
公开(公告)日:2021-05-18
申请号:US16738749
申请日:2020-01-09
申请人: StradVision, Inc.
发明人: Kye-Hyeon Kim , Yongjoong Kim , Hak-Kyoung Kim , Woonhyun Nam , Sukhoon Boo , Myungchul Sung , Dongsoo Shin , Donghun Yeo , Wooju Ryu , Myeong-Chun Lee , Hyungsoo Lee , Taewoong Jang , Kyungjoong Jeong , Hongmo Je , Hojin Cho
摘要: A method for achieving better performance in autonomous driving while saving computing power, by using confidence scores representing a credibility of an object detection which is generated in parallel with an object detection process is provided. And the method includes steps of: (a) a computing device acquiring at least one circumstance image on surroundings of a subject vehicle, through at least one image sensor installed on the subject vehicle; (b) the computing device instructing a convolutional neural network (CNN) to apply at least one CNN operation to the circumstance image, thereby to generate initial object information and initial confidence information on the circumstance image; and (c) the computing device generating final object information on the circumstance image by referring to the initial object information and the initial confidence information with a support of a Reinforcement learning (RL) reinforcement learning (RL) agent, and through V2X communications with at least part of surrounding objects.
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公开(公告)号:US10970598B1
公开(公告)日:2021-04-06
申请号:US17112413
申请日:2020-12-04
申请人: Stradvision, Inc.
发明人: Wooju Ryu , Hongmo Je , Bongnam Kang , Yongjoong Kim
摘要: A method for training an object detection network by using attention maps is provided. The method includes steps of: (a) an on-device learning device inputting the training images into a feature extraction network, inputting outputs of the feature extraction network into a attention network and a concatenation layer, and inputting outputs of the attention network into the concatenation layer; (b) the on-device learning device inputting outputs of the concatenation layer into an RPN and an ROI pooling layer, inputting outputs of the RPN into a binary convertor and the ROI pooling layer, and inputting outputs of the ROI pooling layer into a detection network and thus to output object detection data; and (c) the on-device learning device train at least one of the feature extraction network, the detection network, the RPN and the attention network through backpropagations using an object detection losses, an RPN losses, and a cross-entropy losses.
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公开(公告)号:US10963792B1
公开(公告)日:2021-03-30
申请号:US17111539
申请日:2020-12-04
申请人: Stradvision, Inc.
发明人: Kye-Hyeon Kim , Hongmo Je , Bongnam Kang , Wooju Ryu
摘要: A method for training a deep learning network based on artificial intelligence is provided. The method includes steps of: a learning device (a) inputting unlabeled data into an active learning network to acquire sub unlabeled data and inputting the sub unlabeled data into an auto labeling network to generate new labeled data; (b) allowing a continual learning network to sample the new labeled data and existing labeled data to generate a mini-batch, and train the existing learning network using the mini-batch to acquire a trained learning network, wherein part of the mini-batch are selected by referring to specific existing losses; and (c) (i) allowing an explainable analysis network to generate insightful results on validation data and transmit the insightful results to a human engineer to transmit an analysis of the trained learning network and (ii) modifying at least one of the active learning network and the continual learning network.
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公开(公告)号:US10824947B2
公开(公告)日:2020-11-03
申请号:US16738680
申请日:2020-01-09
申请人: StradVision, Inc.
发明人: Kye-Hyeon Kim , Yongjoong Kim , Hak-Kyoung Kim , Woonhyun Nam , Sukhoon Boo , Myungchul Sung , Dongsoo Shin , Donghun Yeo , Wooju Ryu , Myeong-Chun Lee , Hyungsoo Lee , Taewoong Jang , Kyungjoong Jeong , Hongmo Je , Hojin Cho
摘要: A learning method for supporting a safer autonomous driving through a fusion of information acquired from images and communications is provided. And the method includes steps of: (a) a learning device instructing a first neural network and a second neural network to generate an image-based feature map and a communication-based feature map by using a circumstance image and circumstance communication information; (b) the learning device instructing a third neural network to apply a third neural network operation to the image-based feature map and the communication-based feature map to generate an integrated feature map; (c) the learning device instructing a fourth neural network to apply a fourth neural network operation to the integrated feature map to generate estimated surrounding motion information; and (d) the learning device instructing a first loss layer to train parameters of the first to the fourth neural networks.
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公开(公告)号:US10821897B2
公开(公告)日:2020-11-03
申请号:US16738579
申请日:2020-01-09
申请人: StradVision, Inc.
发明人: Kye-Hyeon Kim , Yongjoong Kim , Hak-Kyoung Kim , Woonhyun Nam , Sukhoon Boo , Myungchul Sung , Dongsoo Shin , Donghun Yeo , Wooju Ryu , Myeong-Chun Lee , Hyungsoo Lee , Taewoong Jang , Kyungjoong Jeong , Hongmo Je , Hojin Cho
摘要: A method for adjusting a position of a driver assistance device according to a driver state is provided. The method includes steps of: a position adjusting device, (a) inputting an upper and a lower body images of a driver, acquired after the driver sits and starts a vehicle, into a pose estimation network, to acquire body keypoints, calculate body part lengths, and adjust a driver's seat position; and (b) while the vehicle is traveling, inputting the upper body image into a face detector to detect a facial part, inputting the facial part into an eye detector to detect an eye part, and inputting the adjusted driver's seat position and 2D coordinates of an eye into a 3D coordinates transforming device, to generate 3D coordinates of the eye referring to the 2D coordinates and the driver's seat position, and adjust a mirror position of the vehicle referring to the 3D coordinates.
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公开(公告)号:US10803333B2
公开(公告)日:2020-10-13
申请号:US16725181
申请日:2019-12-23
申请人: StradVision, Inc.
发明人: Kye-Hyeon Kim , Yongjoong Kim , Hak-Kyoung Kim , Woonhyun Nam , Sukhoon Boo , Myungchul Sung , Dongsoo Shin , Donghun Yeo , Wooju Ryu , Myeong-Chun Lee , Hyungsoo Lee , Taewoong Jang , Kyungjoong Jeong , Hongmo Je , Hojin Cho
摘要: A method for calculating exact location of a subject vehicle by using information on relative distances is provided. And the method includes steps of: (a) a computing device, if a reference image is acquired through a camera on the subject vehicle, detecting reference objects in the reference image; (b) the computing device calculating image-based reference distances between the reference objects and the subject vehicle, by referring to information on reference bounding boxes, corresponding to the reference objects, on the reference image; (c) the computing device (i) generating a distance error value by referring to the image-based reference distances and coordinate-based reference distances, and (ii) calibrating subject location information of the subject vehicle by referring to the distance error value.
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公开(公告)号:US10796571B2
公开(公告)日:2020-10-06
申请号:US16739349
申请日:2020-01-10
申请人: StradVision, Inc.
发明人: Kye-Hyeon Kim , Yongjoong Kim , Hak-Kyoung Kim , Woonhyun Nam , Sukhoon Boo , Myungchul Sung , Dongsoo Shin , Donghun Yeo , Wooju Ryu , Myeong-Chun Lee , Hyungsoo Lee , Taewoong Jang , Kyungjoong Jeong , Hongmo Je , Hojin Cho
IPC分类号: G08G1/0965 , G08G1/04 , G01C21/36 , G05D1/02
摘要: A method for detecting emergency vehicles in real time, and managing subject vehicles to support the emergency vehicles to drive without interferences from the subject vehicles by referring to detected information on the emergency vehicles is provided. And the method includes steps of: (a) a management server generating metadata on the specific emergency vehicle by referring to emergency circumstance information; (b) the management server generating a circumstance scenario vector by referring to the emergency circumstance information and the metadata, comparing the circumstance scenario vector with reference scenario vectors, to thereby find a specific scenario vector whose similarity score with the circumstance scenario vector is larger than a threshold, and acquiring an emergency reaction command by referring to the specific scenario vector; (c) the management server transmitting the emergency reaction command to each of the subject vehicles.
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公开(公告)号:US10748032B1
公开(公告)日:2020-08-18
申请号:US16724617
申请日:2019-12-23
申请人: StradVision, Inc.
发明人: Kye-Hyeon Kim , Yongjoong Kim , Hak-Kyoung Kim , Woonhyun Nam , SukHoon Boo , Myungchul Sung , Dongsoo Shin , Donghun Yeo , Wooju Ryu , Myeong-Chun Lee , Hyungsoo Lee , Taewoong Jang , Kyungjoong Jeong , Hongmo Je , Hojin Cho
摘要: A method for enhancing an accuracy of object distance estimation based on a subject camera by performing pitch calibration of the subject camera more precisely with additional information acquired through V2V communication is provided. And the method includes steps of: (a) a computing device, performing (i) a process of instructing an initial pitch calibration module to apply a pitch calculation operation to the reference image, to thereby generate an initial estimated pitch, and (ii) a process of instructing an object detection network to apply a neural network operation to the reference image, to thereby generate reference object detection information; (b) the computing device instructing an adjusting pitch calibration module to (i) select a target object, (ii) calculate an estimated target height of the target object, (iii) calculate an error corresponding to the initial estimated pitch, and (iv) determine an adjusted estimated pitch on the subject camera by using the error.
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公开(公告)号:US20200252770A1
公开(公告)日:2020-08-06
申请号:US16731953
申请日:2019-12-31
申请人: Stradvision, Inc.
发明人: Kye-Hyeon Kim , Yongjoong Kim , Hak-Kyoung Kim , Woonhyun Nam , SukHoon Boo , Myungchul Sung , Dongsoo Shin , Donghun Yeo , Wooju Ryu , Myeong-Chun Lee , Hyungsoo Lee , Taewoong Jang , Kyungjoong Jeong , Hongmo Je , Hojin Cho
IPC分类号: H04W4/46 , G05D1/00 , G01S13/931
摘要: A method for a V2V communication by using a radar module used for detecting objects nearby is provided. And the method includes steps of: (a) a computing device performing (i) a process of instructing the radar module to transmit 1-st transmitting signals by referring to at least one 1-st schedule and (ii) a process of generating RVA information by using (1-1)-st receiving signals, corresponding to the 1-st transmitting signals; and (b) the computing device performing a process of instructing the radar module to transmit 2-nd transmitting signals by referring to at least one 2-nd schedule.
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