Patents by Inventor Edward Hsiao
Edward Hsiao has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Publication number: 20240129081Abstract: Various schemes pertaining to center 996-tone resource unit (RU996) tone plan designs for wide bandwidth 240 MHz in wireless communications are described. A communication entity generates at least one 996-tone resource unit (RU996). The communication entity then communicates wirelessly using the at least one RU996 in a 240 MHz bandwidth. The at least one RU996 includes a center RU996 that is centered around five or more direct-current (DC) tones.Type: ApplicationFiled: October 4, 2023Publication date: April 18, 2024Inventors: Shengquan Hu, Ching-Wen Hsiao, Jianhan Liu, Thomas Edward Pare, Jr.
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Patent number: 11941519Abstract: Aspects of the disclosure relate to training a machine learning model on a distributed computing system. The model can be trained using selected processors of the training platform. The distributed system automatically modifies the model for instantiation on each processor, adjusts an input pipeline to accommodate the capabilities of selected processors, and coordinates the training between those processors. Simultaneous processing at each stage can be scaled to reduce or eliminate bottlenecks in the distributed system. In addition, autonomous monitoring and re-allocating of resources can further reduce or eliminate bottlenecks. The training results may be aggregated by the distributed system, and a final model may then be transmitted to a user device.Type: GrantFiled: December 2, 2019Date of Patent: March 26, 2024Assignee: Waymo LLCInventors: Pok Man Chu, Edward Hsiao
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Publication number: 20240092392Abstract: Aspects of the disclosure relate to detecting and responding to malfunctioning traffic signals for a vehicle having an autonomous driving mode. For instance, information identifying a detected state of a traffic signal for an intersection. An anomaly for the traffic signal may be detected based on the detected state and prestored information about expected states of the traffic signal. The vehicle may be controlled in the autonomous driving mode based on the detected anomaly.Type: ApplicationFiled: November 29, 2023Publication date: March 21, 2024Inventors: David Silver, Carl Kershaw, Jonathan Hsiao, Edward Hsiao
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Publication number: 20240075959Abstract: Aspects of the disclosure relate to controlling a vehicle having an autonomous driving mode. For instance, a current state of a traffic light may be determined. One of a plurality of yellow light durations may be selected based on the current state of the traffic light. When the traffic light will turn red may be predicted based on the selected one. The prediction may be used to control the vehicle in the autonomous driving mode.Type: ApplicationFiled: November 8, 2023Publication date: March 7, 2024Inventors: Edward Hsiao, Maoqing Yao, David Margines, Yosuke Higashi
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Patent number: 11866068Abstract: Aspects of the disclosure relate to detecting and responding to malfunctioning traffic signals for a vehicle having an autonomous driving mode. For instance, information identifying a detected state of a traffic signal for an intersection. An anomaly for the traffic signal may be detected based on the detected state and prestored information about expected states of the traffic signal. The vehicle may be controlled in the autonomous driving mode based on the detected anomaly.Type: GrantFiled: June 19, 2020Date of Patent: January 9, 2024Assignee: Waymo LLCInventors: David Silver, Carl Kershaw, Jonathan Hsiao, Edward Hsiao
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Patent number: 11845469Abstract: Aspects of the disclosure relate to controlling a vehicle having an autonomous driving mode. For instance, a current state of a traffic light may be determined. One of a plurality of yellow light durations may be selected based on the current state of the traffic light. When the traffic light will turn red may be predicted based on the selected one. The prediction may be used to control the vehicle in the autonomous driving mode.Type: GrantFiled: June 29, 2020Date of Patent: December 19, 2023Assignee: Waymo LLCInventors: Edward Hsiao, Maoqing Yao, David Margines, Yosuke Higashi
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Patent number: 11783596Abstract: Machine-learning models are described detecting the signaling state of a traffic signaling unit. A system can obtain an image of the traffic signaling unit, and select a model of the traffic signaling unit that identifies a position of each traffic lighting element on the unit. First and second neural network inputs are processed with a neural network to generate an estimated signaling state of the traffic signaling unit. The first neural network input can represent the image of the traffic signaling unit, and the second neural network input can represent the model of the traffic signaling unit. Using the estimated signaling state of the traffic signaling unit, the system can inform a driving decision of a vehicle.Type: GrantFiled: May 6, 2022Date of Patent: October 10, 2023Assignee: Waymo LLCInventors: Edward Hsiao, Yu Ouyang, Maoqing Yao
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Patent number: 11645852Abstract: Methods and system are provided for training and using a model to determine states of lanes of interest. For instance, image data including an image and an associated label identifying at least one traffic light, a state of the at least one traffic light, and a lane controlled by the at least one traffic light are received and used to train the model such that the model is configured to, in response to receiving an image and a lane of interest included in the image, output a lane state for the lane of interest. This model is then used by a vehicle in order to determine a state of a lane of interest. This state is then used to control the vehicle in an autonomous driving mode based on the state of the lane of interest.Type: GrantFiled: June 2, 2021Date of Patent: May 9, 2023Assignee: Waymo LLCInventors: Maxim Krivokon, Abhijit S. Ogale, Edward Hsiao, Andreas Wendel
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Publication number: 20220335731Abstract: Machine-learning models are described detecting the signaling state of a traffic signaling unit. A system can obtain an image of the traffic signaling unit, and select a model of the traffic signaling unit that identifies a position of each traffic lighting element on the unit. First and second neural network inputs are processed with a neural network to generate an estimated signaling state of the traffic signaling unit. The first neural network input can represent the image of the traffic signaling unit, and the second neural network input can represent the model of the traffic signaling unit. Using the estimated signaling state of the traffic signaling unit, the system can inform a driving decision of a vehicle.Type: ApplicationFiled: May 6, 2022Publication date: October 20, 2022Inventors: Edward Hsiao, Yu Ouyang, Maoqing Yao
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Patent number: 11328519Abstract: Machine-learning models are described detecting the signaling state of a traffic signaling unit. A system can obtain an image of the traffic signaling unit, and select a model of the traffic signaling unit that identifies a position of each traffic lighting element on the unit. First and second neural network inputs are processed with a neural network to generate an estimated signaling state of the traffic signaling unit. The first neural network input can represent the image of the traffic signaling unit, and the second neural network input can represent the model of the traffic signaling unit. Using the estimated signaling state of the traffic signaling unit, the system can inform a driving decision of a vehicle.Type: GrantFiled: July 23, 2020Date of Patent: May 10, 2022Assignee: Waymo LLCInventors: Edward Hsiao, Yu Ouyang, Maoqing Yao
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Publication number: 20220121216Abstract: The technology relates to controlling a vehicle based on a railroad light's activation status. In one example, one or more processors receive images of a railroad light. The one or more processors determine, based on the images of the railroad light, the illumination status of a pair of lights of the railroad light over a period of time as the vehicle approaches the railroad light. The one or more processors determine based on the illumination status of the pair of lights, a confidence level, wherein the confidence level indicates the likelihood the railroad light is active. The vehicle is controlled as it approaches the railroad light based on the confidence level.Type: ApplicationFiled: January 3, 2022Publication date: April 21, 2022Inventor: Edward Hsiao
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Patent number: 11249487Abstract: The technology relates to controlling a vehicle based on a railroad light's activation status. In one example, one or more processors receive images of a railroad light. The one or more processors determine, based on the images of the railroad light, the illumination status of a pair of lights of the railroad light over a period of time as the vehicle approaches the railroad light. The one or more processors determine based on the illumination status of the pair of lights, a confidence level, wherein the confidence level indicates the likelihood the railroad light is active. The vehicle is controlled as it approaches the railroad light based on the confidence level.Type: GrantFiled: October 26, 2018Date of Patent: February 15, 2022Assignee: Waymo LLCInventor: Edward Hsiao
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Publication number: 20220027645Abstract: Machine-learning models are described detecting the signaling state of a traffic signaling unit. A system can obtain an image of the traffic signaling unit, and select a model of the traffic signaling unit that identifies a position of each traffic lighting element on the unit. First and second neural network inputs are processed with a neural network to generate an estimated signaling state of the traffic signaling unit. The first neural network input can represent the image of the traffic signaling unit, and the second neural network input can represent the model of the traffic signaling unit. Using the estimated signaling state of the traffic signaling unit, the system can inform a driving decision of a vehicle.Type: ApplicationFiled: July 23, 2020Publication date: January 27, 2022Inventors: Edward Hsiao, Yu Ouyang, Maoqing Yao
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Publication number: 20210403047Abstract: Aspects of the disclosure relate to controlling a vehicle having an autonomous driving mode. For instance, a current state of a traffic light may be determined. One of a plurality of yellow light durations may be selected based on the current state of the traffic light. When the traffic light will turn red may be predicted based on the selected one. The prediction may be used to control the vehicle in the autonomous driving mode.Type: ApplicationFiled: June 29, 2020Publication date: December 30, 2021Inventors: Edward Hsiao, Maoqing Yao, David Margines, Yosuke Higashi
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Publication number: 20210397827Abstract: Aspects of the disclosure relate to detecting and responding to malfunctioning traffic signals for a vehicle having an autonomous driving mode. For instance, information identifying a detected state of a traffic signal for an intersection. An anomaly for the traffic signal may be detected based on the detected state and prestored information about expected states of the traffic signal. The vehicle may be controlled in the autonomous driving mode based on the detected anomaly.Type: ApplicationFiled: June 19, 2020Publication date: December 23, 2021Inventors: David Silver, Carl Kershaw, Jonathan Hsiao, Edward Hsiao
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Publication number: 20210343150Abstract: Methods and system are provided for training and using a model to determine states of lanes of interest. For instance, image data including an image and an associated label identifying at least one traffic light, a state of the at least one traffic light, and a lane controlled by the at least one traffic light are received and used to train the model such that the model is configured to, in response to receiving an image and a lane of interest included in the image, output a lane state for the lane of interest. This model is then used by a vehicle in order to determine a state of a lane of interest. This state is then used to control the vehicle in an autonomous driving mode based on the state of the lane of interest.Type: ApplicationFiled: June 2, 2021Publication date: November 4, 2021Inventors: Maxim Krivokon, Abhijit S. Ogale, Edward Hsiao, Andreas Wendel
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Patent number: 11056005Abstract: Methods and system are provided for training and using a model to determine states of lanes of interest. For instance, image data including an image and an associated label identifying at least one traffic light, a state of the at least one traffic light, and a lane controlled by the at least one traffic light are received and used to train the model such that the model is configured to, in response to receiving an image and a lane of interest included in the image, output a lane state for the lane of interest. This model is then used by a vehicle in order to determine a state of a lane of interest. This state is then used to control the vehicle in an autonomous driving mode based on the state of the lane of interest.Type: GrantFiled: October 24, 2018Date of Patent: July 6, 2021Assignee: Waymo LLCInventors: Maxim Krivokon, Abhijit S. Ogale, Edward Hsiao, Andreas Wendel
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Publication number: 20210166117Abstract: Aspects of the disclosure relate to training a machine learning model on a distributed computing system. The model can be trained using selected processors of the training platform. The distributed system automatically modifies the model for instantiation on each processor, adjusts an input pipeline to accommodate the capabilities of selected processors, and coordinates the training between those processors. Simultaneous processing at each stage can be scaled to reduce or eliminate bottlenecks in the distributed system. In addition, autonomous monitoring and re-allocating of resources can further reduce or eliminate bottlenecks. The training results may be aggregated by the distributed system, and a final model may then be transmitted to a user device.Type: ApplicationFiled: December 2, 2019Publication date: June 3, 2021Inventors: Pok Man Chu, Edward Hsiao
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Patent number: 10956784Abstract: An image creation and editing tool can use the data produced from training a neural network to add stylized representations of an object to an image. An object classification will correspond to an object representation, and pixel values for the object representation can be added to, or blended with, the pixel values of an image in order to add a visualization of a type of object to the image. Such an approach can be used to add stylized representations of objects to existing images or create new images based on those representations. The visualizations can be used to create patterns and textures as well, as may be used to paint or fill various regions of an image. Such patterns can enable regions to be filled where image data has been deleted, such as to remove an undesired object, in a way that appears natural for the contents of the image.Type: GrantFiled: December 17, 2018Date of Patent: March 23, 2021Assignee: A9.COM, INC.Inventors: Douglas Ryan Gray, Alexander Li Honda, Edward Hsiao
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Patent number: 10650040Abstract: An object recognition system can be adapted to recognize subject matter having very few features or limited or no texture. A feature-sparse or texture-limited object can be recognized by complementing local features and/or texture features with color, region-based, shape-based, three-dimensional (3D), global, and/or composite features. Machine learning algorithms can be used to classify such objects, and image matching and verification can be adapted to the classification. Further, multiple modes of input can be integrated at various stages of the object recognition processing pipeline. These multi-modal inputs can include user feedback, additional images representing different perspectives of the object or specific regions of the object including a logo or text corresponding to the object, user behavior data, location, among others.Type: GrantFiled: May 22, 2017Date of Patent: May 12, 2020Assignee: A9.com, Inc.Inventors: Simant Dube, Edward Hsiao