SEARCH RESULTS for assignor:"KIM, KYE-HYEON; KIM, YONGJOONG; KIM, INSU; KIM, HAK-KYOUNG; NAM, WOONHYUN; BOO, SUKHOON; SUNG, MYUNGCHUL; YEO, DONGHUN; RYU, WOOJU; JANG, TAEWOONG; JEONG, KYUNGJOONG; JE, HONGMO; CHO, HOJIN" AND day:[2019-08-06T00:00:00Z TO 2019-08-06T23:59:59Z]

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(X0) 16260244: METHOD AND DEVICE FOR MERGING OBJECT DETECTION INFORMATION DETECTED BY EACH OF OBJECT DETECTORS CORRESPONDING TO EACH CAMERA NEARBY FOR THE PURPOSE OF COLLABORATIVE DRIVING BY USING V2X-ENABLED APPLICATIONS, SENSOR FUSION VIA MULTIPLE VEHICLES

(B1) 1: METHOD AND DEVICE FOR MERGING OBJECT DETECTION INFORMATION DETECTED BY EACH OF OBJECT DETECTORS CORRESPONDING TO EACH CAMERA NEARBY FOR THE PURPOSE OF COLLABORATIVE DRIVING BY USING V2X-ENABLED APPLICATIONS, SENSOR FUSION VIA MULTIPLE VEHICLES

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(X0) 16259355: LEARNING METHOD AND LEARNING DEVICE FOR GENERATION OF VIRTUAL FEATURE MAPS WHOSE CHARACTERISTICS ARE SAME AS OR SIMILAR TO THOSE OF REAL FEATURE MAPS BY USING GAN CAPABLE OF BEING APPLIED TO DOMAIN ADAPTATION TO BE USED IN VIRTUAL DRIVING ENVIRONMENTS

(B1) 1: LEARNING METHOD AND LEARNING DEVICE FOR GENERATION OF VIRTUAL FEATURE MAPS WHOSE CHARACTERISTICS ARE SAME AS OR SIMILAR TO THOSE OF REAL FEATURE MAPS BY USING GAN CAPABLE OF BEING APPLIED TO DOMAIN ADAPTATION TO BE USED IN VIRTUAL DRIVING ENVIRONMENTS

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(X0) 16258877: LEARNING METHOD AND LEARNING DEVICE FOR RUNTIME INPUT TRANSFORMATION OF REAL IMAGE ON REAL WORLD INTO VIRTUAL IMAGE ON VIRTUAL WORLD, TO BE USED FOR OBJECT DETECTION ON REAL IMAGES, BY USING CYCLE GAN CAPABLE OF BEING APPLIED TO DOMAIN ADAPTATION

(B1) 1: LEARNING METHOD AND LEARNING DEVICE FOR RUNTIME INPUT TRANSFORMATION OF REAL IMAGE ON REAL WORLD INTO VIRTUAL IMAGE ON VIRTUAL WORLD, TO BE USED FOR OBJECT DETECTION ON REAL IMAGES, BY USING CYCLE GAN CAPABLE OF BEING APPLIED TO DOMAIN ADAPTATION

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(X0) 16263123: METHOD AND DEVICE FOR DETECTING LANE ELEMENTS TO PLAN THE DRIVE PATH OF AUTONOMOUS VEHICLE BY USING A HORIZONTAL FILTER MASK, WHEREIN THE LANE ELEMENTS ARE UNIT REGIONS INCLUDING PIXELS OF LANES IN AN INPUT IMAGE

(B1) 1: METHOD AND DEVICE FOR DETECTING LANE ELEMENTS TO PLAN THE DRIVE PATH OF AUTONOMOUS VEHICLE BY USING A HORIZONTAL FILTER MASK, WHEREIN THE LANE ELEMENTS ARE UNIT REGIONS INCLUDING PIXELS OF LANES IN AN INPUT IMAGE

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(X0) 16254545: LEARNING METHOD AND LEARNING DEVICE FOR ATTENTION-DRIVEN IMAGE SEGMENTATION BY USING AT LEAST ONE ADAPTIVE LOSS WEIGHT MAP TO BE USED FOR UPDATING HD MAPS REQUIRED TO SATISFY LEVEL 4 OF AUTONOMOUS VEHICLES AND TESTING METHOD AND TESTING DEVICE USING THE SAME

(B1) 1: LEARNING METHOD AND LEARNING DEVICE FOR ATTENTION-DRIVEN IMAGE SEGMENTATION BY USING AT LEAST ONE ADAPTIVE LOSS WEIGHT MAP TO BE USED FOR UPDATING HD MAPS REQUIRED TO SATISFY LEVEL 4 OF AUTONOMOUS VEHICLES AND TESTING METHOD AND TESTING DEVICE USING THE SAME

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(X0) 16258837: METHOD AND DEVICE FOR VERIFYING INTEGRITY OF PARAMETERS OF CNN BY USING TEST PATTERN TO ENHANCE FAULT TOLERANCE AND FLUCTUATION ROBUSTNESS IN EXTREME SITUATIONS FOR FUNCTIONAL SAFETY

(B1) 1: METHOD AND DEVICE FOR VERIFYING INTEGRITY OF PARAMETERS OF CNN BY USING TEST PATTERN TO ENHANCE FAULT TOLERANCE AND FLUCTUATION ROBUSTNESS IN EXTREME SITUATIONS FOR FUNCTIONAL SAFETY

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(X0) 16258841: METHOD AND DEVICE FOR GENERATING TEST PATTERNS AND SELECTING OPTIMIZED TEST PATTERNS AMONG THE TEST PATTERNS IN ORDER TO VERIFY INTEGRITY OF CONVOLUTION OPERATIONS TO ENHANCE FAULT TOLERANCE AND FLUCTUATION ROBUSTNESS IN EXTREME SITUATIONS

(B1) 1: METHOD AND DEVICE FOR GENERATING TEST PATTERNS AND SELECTING OPTIMIZED TEST PATTERNS AMONG THE TEST PATTERNS IN ORDER TO VERIFY INTEGRITY OF CONVOLUTION OPERATIONS TO ENHANCE FAULT TOLERANCE AND FLUCTUATION ROBUSTNESS IN EXTREME SITUATIONS

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