Patents by Inventor Yudong Liang
Yudong Liang 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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Patent number: 12277503Abstract: A system for image quality assessment of non-aligned images includes a first deep path portion of a convolutional neural network having a set of parameters and a second deep path portion of the convolutional neural network sharing a set of parameters with the first deep path convolutional neural network. Weights are shared between the first and second deep path convolutional neural networks to support extraction of a same set of features in each neural network pathway. Non-aligned reference and distorted images are respectively provided to the first and second deep paths of the convolutional neural network for processing. A concatenation layer is connected to both the first and second deep paths convolutional neural network, and a fully connected layer is connected to the concatenation layer to receive input from both the first and second deep paths of the convolutional neural network, generating an image quality assessment as a linear regressor and outputting an image quality score.Type: GrantFiled: October 16, 2023Date of Patent: April 15, 2025Assignee: DeepNorth Inc.Inventors: Jinjun Wang, Yudong Liang
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Patent number: 12269253Abstract: A heat press machine includes a base, an extension arm and a heating plate. The base is provided with a first carrier plate and a second carrier plate, the extension arm is rotatably mounted on the base, the extension arm is provided with a lifting assembly, and the lifting assembly is connected to the heating plate and used for driving the heating plate to ascend and descend. A commodity to be pressed is fixed by disposing two carrier plates on the base, the movement of the heating plate above the two carrier plates is achieved by the rotatable extension arm, after the commodity on one of the carrier plates is pressed, the heating plate may be moved to be above the other carrier plate to press the commodity in processes of loading, unloading and laminating the commodity by an operator, thereby improving the printing efficiency.Type: GrantFiled: October 23, 2024Date of Patent: April 8, 2025Inventor: Yudong Liang
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Publication number: 20250042147Abstract: A heat transfer machine includes a base, an extension arm and a heating plate. The base is provided with a first carrier plate and a second carrier plate, the extension arm is rotatably mounted on the base, the extension arm is provided with a lifting assembly, and the lifting assembly is connected to the heating plate and used for driving the heating plate to ascend and descend. A commodity to be transferred is fixed by disposing two carrier plates on the base, the movement of the heating plate above the two carrier plates is achieved by the rotatable extension arm, after the commodity on one of the carrier plates is transferred, the heating plate may be moved to be above the other carrier plate to transfer the commodity in processes of loading, unloading and laminating the commodity by an operator, thereby improving the printing efficiency.Type: ApplicationFiled: October 23, 2024Publication date: February 6, 2025Inventor: Yudong LIANG
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Publication number: 20240046105Abstract: A system for image quality assessment of non-aligned images includes a first deep path portion of a convolutional neural network having a set of parameters and a second deep path portion of the convolutional neural network sharing a set of parameters with the first deep path convolutional neural network. Weights are shared between the first and second deep path convolutional neural networks to support extraction of a same set of features in each neural network pathway. Non-aligned reference and distorted images are respectively provided to the first and second deep paths of the convolutional neural network for processing. A concatenation layer is connected to both the first and second deep paths convolutional neural network, and a fully connected layer is connected to the concatenation layer to receive input from both the first and second deep paths of the convolutional neural network, generating an image quality assessment as a linear regressor and outputting an image quality score.Type: ApplicationFiled: October 16, 2023Publication date: February 8, 2024Inventors: Jinjun Wang, Yudong Liang
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Patent number: 11816576Abstract: A system for image quality assessment of non-aligned images includes a first deep path portion of a convolutional neural network having a set of parameters and a second deep path portion of the convolutional neural network sharing a set of parameters with the first deep path convolutional neural network. Weights are shared between the first and second deep path convolutional neural networks to support extraction of a same set of features in each neural network pathway. Non-aligned reference and distorted images are respectively provided to the first and second deep paths of the convolutional neural network for processing. A concatenation layer is connected to both the first and second deep paths convolutional neural network, and a fully connected layer is connected to the concatenation layer to receive input from both the first and second deep paths of the convolutional neural network, generating an image quality assessment as a linear regressor and outputting an image quality score.Type: GrantFiled: July 20, 2021Date of Patent: November 14, 2023Assignee: DEEP NORTH, INC.Inventors: Jinjun Wang, Yudong Liang
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Publication number: 20210350243Abstract: A system for image quality assessment of non-aligned images includes a first deep path portion of a convolutional neural network having a set of parameters and a second deep path portion of the convolutional neural network sharing a set of parameters with the first deep path convolutional neural network. Weights are shared between the first and second deep path convolutional neural networks to support extraction of a same set of features in each neural network pathway. Non-aligned reference and distorted images are respectively provided to the first and second deep paths of the convolutional neural network for processing. A concatenation layer is connected to both the first and second deep paths convolutional neural network, and a fully connected layer is connected to the concatenation layer to receive input from both the first and second deep paths of the convolutional neural network, generating an image quality assessment as a linear regressor and outputting an image quality score.Type: ApplicationFiled: July 20, 2021Publication date: November 11, 2021Inventors: Jinjun Wang, Yudong Liang
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Patent number: 11100402Abstract: A system for image quality assessment of non-aligned images includes a first deep path portion of a convolutional neural network having a set of parameters and a second deep path portion of the convolutional neural network sharing a set of parameters with the first deep path convolutional neural network. Weights are shared between the first and second deep path convolutional neural networks to support extraction of a same set of features in each neural network pathway. Non-aligned reference and distorted images are respectively provided to the first and second deep paths of the convolutional neural network for processing. A concatenation layer is connected to both the first and second deep paths convolutional neural network, and a fully connected layer is connected to the concatenation layer to receive input from both the first and second deep paths of the convolutional neural network, generating an image quality assessment as a linear regressor and outputting an image quality score.Type: GrantFiled: January 16, 2020Date of Patent: August 24, 2021Assignee: DEEP NORTH, INC.Inventors: Jinjun Wang, Yudong Liang
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Publication number: 20200280115Abstract: An integrated filter system, including: a dielectric slab assembly; and a filter circuit arranged on the dielectric slab assembly, where the filter circuit includes a low-pass filter and a band-pass filter connected to one another in series. The present invention further discloses an antenna system. By means of the foregoing implementations, the filter system and the antenna system are integrated and miniaturized and have smaller weights, and the filter system and the antenna system have a simple structure and lower costs, and stable and reliable whole performance.Type: ApplicationFiled: January 20, 2017Publication date: September 3, 2020Applicants: TONGYU COMMUNICATION INC., TONGYU COMMUNICATION INC.Inventors: Hui CAI, Pengbo WANG, Qi ZHOU, Jianzhao YU, Yudong LIANG, Qilue FU, Gang JU
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Publication number: 20200234141Abstract: A system for image quality assessment of non-aligned images includes a first deep path portion of a convolutional neural network having a set of parameters and a second deep path portion of the convolutional neural network sharing a set of parameters with the first deep path convolutional neural network. Weights are shared between the first and second deep path convolutional neural networks to support extraction of a same set of features in each neural network pathway. Non-aligned reference and distorted images are respectively provided to the first and second deep paths of the convolutional neural network for processing. A concatenation layer is connected to both the first and second deep paths convolutional neural network, and a fully connected layer is connected to the concatenation layer to receive input from both the first and second deep paths of the convolutional neural network, generating an image quality assessment as a linear regressor and outputting an image quality score.Type: ApplicationFiled: January 16, 2020Publication date: July 23, 2020Inventors: Jinjun Wang, Yudong Liang
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Patent number: 10540589Abstract: A system for image quality assessment of non-aligned images includes a first deep path portion of a convolutional neural network having a set of parameters and a second deep path portion of the convolutional neural network sharing a set of parameters with the first deep path convolutional neural network. Weights are shared between the first and second deep path convolutional neural networks to support extraction of a same set of features in each neural network pathway. Non-aligned reference and distorted images are respectively provided to the first and second deep paths of the convolutional neural network for processing. A concatenation layer is connected to both the first and second deep paths convolutional neural network, and a fully connected layer is connected to the concatenation layer to receive input from both the first and second deep paths of the convolutional neural network, generating an image quality assessment as a linear regressor and outputting an image quality score.Type: GrantFiled: October 24, 2017Date of Patent: January 21, 2020Assignee: DEEP NORTH, INC.Inventors: Jinjun Wang, Yudong Liang
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Publication number: 20190122115Abstract: A system for image quality assessment of non-aligned images includes a first deep path portion of a convolutional neural network having a set of parameters and a second deep path portion of the convolutional neural network sharing a set of parameters with the first deep path convolutional neural network. Weights are shared between the first and second deep path convolutional neural networks to support extraction of a same set of features in each neural network pathway. Non-aligned reference and distorted images are respectively provided to the first and second deep paths of the convolutional neural network for processing. A concatenation layer is connected to both the first and second deep paths convolutional neural network, and a fully connected layer is connected to the concatenation layer to receive input from both the first and second deep paths of the convolutional neural network, generating an image quality assessment as a linear regressor and outputting an image quality score.Type: ApplicationFiled: October 24, 2017Publication date: April 25, 2019Inventors: Jinjun Wang, Yudong Liang
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Patent number: D734879Type: GrantFiled: March 7, 2014Date of Patent: July 21, 2015Assignee: Zhejiang Shengui Lighting Co, Ltd.Inventors: Liang Chen, Yudong Liang, Yinxiao Zhu
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Patent number: D982623Type: GrantFiled: October 21, 2021Date of Patent: April 4, 2023Assignee: Guangzhou Jingwushi Information Technology Co., Ltd.Inventors: Yudong Liang, De Zhang
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Patent number: D1051189Type: GrantFiled: June 21, 2024Date of Patent: November 12, 2024Inventor: Yudong Liang