Systems and methods for training generative adversarial networks and use of trained generative adversarial networks

A generative, network technology, applied in the field of network and neural network, can solve the problem of difficult real-time application of the system, and achieve the effect of good specialization, high accuracy and efficiency

Pending Publication Date: 2021-03-23
科斯默人工智能 AI有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

As a result, these systems are often difficult to implement in the required real-time manner

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  • Systems and methods for training generative adversarial networks and use of trained generative adversarial networks
  • Systems and methods for training generative adversarial networks and use of trained generative adversarial networks
  • Systems and methods for training generative adversarial networks and use of trained generative adversarial networks

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Embodiment Construction

[0039] The disclosed embodiments relate to computer-implemented systems and methods for training and using generative adversarial networks. Advantageously, the exemplary embodiments may provide improved training networks and fast and efficient object detection. Embodiments of the present disclosure may also provide improved object detection with reduced false positives for medical image analysis.

[0040] Embodiments of the present disclosure can be implemented and used in a variety of applications and vision systems. For example, embodiments of the present disclosure may be implemented for medical image analysis systems and other types of systems that benefit from object detection where objects may be true positives or false positives. Although embodiments of the present disclosure are generally described herein with reference to medical image analysis and endoscopy, it should be understood that the embodiments are also applicable to other medical imaging procedures such as ...

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Abstract

The present disclosure relates to systems and methods for training generative adversarial networks and use of trained generative adversarial networks. In one implementation, a system for training a generative adversarial network may include at least one processor that may provide a first plurality of images including representations of a feature-of-interest and indicators of locations of the feature-of-interest and use the first plurality and indicators to train an object detection network. Further, the processor(s) may provide a second plurality of images including representations of the feature-of-interest, and apply the trained object detection network to the second plurality to produce a plurality of detection of the feature-of-interest. Additionally, the processor(s) may provide manually set verification of true positives and false positives with respect to the plurality of detection, use the verification to train a generative adversarial network, and retrain the generative adversarial network using at least one further set of images, further detection, and further manually set verification.

Description

technical field [0001] The present disclosure relates generally to the field of neural networks and to the use of such networks for image analysis and object detection. More specifically, but not limitation, the present disclosure relates to systems and methods for training generative adversarial networks and computer-implemented systems and methods using such generative adversarial networks. The systems, methods, and trained neural networks disclosed herein can be used in various applications and vision systems, such as medical image analysis and systems that benefit from accurate object detection capabilities. Background technique [0002] In many object detection systems, objects are detected in images. Objects of interest can be people, places, or things. Localization of objects is also important in applications such as medical image analysis and diagnosis. However, computer-implemented systems utilizing image classifiers typically cannot recognize or provide the loca...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62
CPCG06V2201/031G06F18/2413G06N3/08G06T7/0012G06T2207/30096G06T2207/10068A61B1/273G06T2207/30032G06T2207/20081A61B1/00009G06F18/217G06F18/214A61B1/00043A61B1/00055A61B1/31G06N3/04G16H50/20G16H30/40A61B1/2736G06N3/088G06T2207/10016G06T2207/20084G06V2201/032A61B1/000096G06F18/41G06F18/2148G06N3/045
Inventor N·吴丁朱利奥·伊万吉利斯提弗拉维奥·纳瓦里
Owner 科斯默人工智能 AI有限公司
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