公开(公告)号：EP4502732A1

公开(公告)日：2025-02-05

申请号：EP23189164.9

申请日：2023-08-02

Applicant: BIOMÉRIEUX ,  Bioaster ,  Université Jean Monnet Saint-Étienne ,  Centre National de la Recherche Scientifique (CNRS)

Inventor： BRAULT, Dylan ,  FOURNIER, Corinne ,  OLIVIER, Thomas ,  FAURE, Nicolas

IPC: G03H1/00 ,  G03H1/04 ,  G03H1/26 ,  G01N15/1433 ,  G01N15/1434 ,  G01N15/10 ,  G03H1/08 ,  G06T7/00 ,  G06V10/143 ,  G06V10/22 ,  G06V10/24 ,  G06V10/26 ,  G06V10/44 ,  C12Q1/04

Abstract: Un procédé de caractérisation de microorganismes comprend
A. pour chaque longueur d'onde d'un ensemble prédéterminé de longueurs d'onde d'au moins une longueur d'onde, l'acquisition d'une image numérique holographique la génération informatique d'une image focalisée dont chaque pixel comprend une valeur d'amplitude et une valeur de phase, la segmentation de l'image focalisée de manière à extraire des portions correspondant à des microorganismes;
B. la caractérisation informatique des microorganismes en fonction desdites portions d'images focalisées,
Selon l'invention, préalablement à la caractérisation ou préalablement à la segmentation ou préalablement à la génération de l'image focalisée, le procédé comporte la correction informatique d'aberrations optiques du dispositif d'acquisition et la caractérisation des microorganismes comporte l'application d'un modèle numérique auxdites portions ayant pour descripteurs les valeurs d'amplitude et/ou de phase de chaque longueur d'onde de l'ensemble prédéterminé de longueurs d'onde.

公开(公告)号：EP4485368A1

公开(公告)日：2025-01-01

申请号：EP24183139.5

申请日：2024-06-19

Applicant: Accenture Global Solutions Limited

Inventor： CHA, Sujeong ,  VADLAMANI, Surya Raghavendra ,  KANG, Sukryool ,  Anupam Anurag, TRIPATHI ,  MOHAMED, Suhail ,  SMITH, Peter Royer, Jr ,  ZHANG, Bo ,  GARRISON, Daniel ,  SINGH, Jatinder ,  DANG, Neha Wadhwa

IPC: G06V10/26 ,  G06V10/42 ,  G06V10/74 ,  G06V10/82 ,  G06V20/70

Abstract: Described herein are systems, methods, devices, and other techniques for comprehensive and automated evaluation of digital images generated from artificial intelligence (Al) models in order to promote accurate representations of real-world content. Prompts are received at the system that are then passed to both a search engine and a generative Al model. Synthesized digital images are obtained from the generative Al model. The top-matching image from the search engine is used as a verification of the ground truth of the synthesized digital images. A realism score is generated for each synthesized digital image that characterizes the accuracy of the synthesized digital image with reference to the verification image. The realism score can be used to assist and expedite the image selection process, as well as serve as input to fine-tune the performance of generative models.

公开(公告)号：EP4113459B1

公开(公告)日：2025-01-01

申请号：EP21206396.0

申请日：2021-11-04

Inventor： Schiffer, Stefan ,  Naujeck, Marcel

IPC: G06V20/54 ,  G06V20/50 ,  G06V10/62 ,  G06V10/26 ,  G06V10/20

公开(公告)号：EP4465248A1

公开(公告)日：2024-11-20

申请号：EP23173346.0

申请日：2023-05-15

Applicant: Axis AB

Inventor： Danielsson, Niclas ,  Colliander, Christian ,  Nilsson, Amanda ,  Laross, Sarah

IPC: G06V10/25 ,  G06V10/26 ,  G06V10/36 ,  G06V10/46 ,  G06V10/62 ,  G06V20/52 ,  G06T7/20

Abstract: The present disclosure relates to methods for prioritizing feature extraction for object re-identification in an object tracking application. Region of interests, ROI, 110, 116 for object feature extraction is determined based on motion areas in the image frame 100a-e. Each object 102, 104, 112 detected in an image frame and which is at least partly overlapping with a ROI is associated with the ROI. A list of candidate objects for feature extraction is determined by, for each ROI associated with two or more objects: adding each object of the two or more objects that is not overlapping with any of the other objects among the two or more objects with more than a threshold amount. From the list of candidate objects, at least one object is selected, and image data of the image frame depicting the selected object is used for determining a feature vector for the selected object.

公开(公告)号：EP4465113A1

公开(公告)日：2024-11-20

申请号：EP24174549.6

申请日：2024-05-07

Applicant: Apple Inc.

Inventor： CAO, Renbo ,  ZHAO, Yonghui ,  BAI, Yingjun ,  SEYVE, Christophe ,  BLASINSKI, Henryk

IPC: G02B27/01 ,  G06V10/26 ,  H04N23/71 ,  H04N23/73 ,  H04N23/76 ,  H04N23/81

Abstract: An apparatus can include a first image sensor having a first field of view (FOV) and configured to capture a first image, a second image sensor having a second FOV and configured to capture a second image, an image statistics collection subsystem configured to gather first image statistics information associated with the first image and to gather second image statistics information associated with the second image, a disparity detection subsystem configured to compare the first image statistics information with the second image statistics information, and image signal processing blocks configured to synchronize processing of the first and second images based on the comparison of the first image statistics information with the second image statistics information. Processing of the first and second images can involve using one or more combined image signal processing control parameters based on image statistics information within an overlapping FOV and/or a within a total FOV.

公开(公告)号：EP4148666B1

公开(公告)日：2024-11-06

申请号：EP21208678.9

申请日：2021-11-17

Inventor： HUANG, Shih-Ho ,  YIN, Ming-Tzuo

IPC: G06T7/12 ,  G06T7/181 ,  G06V10/82 ,  G06V10/26

公开(公告)号：EP3963508B1

公开(公告)日：2024-09-18

申请号：EP20802574.2

申请日：2020-05-01

IPC: G06N3/02 ,  G06N3/04 ,  G06N3/08 ,  G06T7/00 ,  G06T7/10 ,  G06F18/243 ,  G06T7/11 ,  G06V10/25 ,  G06V10/26 ,  G06V10/44 ,  G06V10/764 ,  G06V10/82 ,  G16H30/40 ,  G16H40/67 ,  G16H50/20 ,  G06V10/778

CPC classification number: G16H30/40 ,  G16H40/67 ,  G16H50/20 ,  G06T7/0012 ,  G06T7/11 ,  G06T2200/2420130101 ,  G06T2207/1005620130101 ,  G06T2207/2001620130101 ,  G06T2207/2002120130101 ,  G06T2207/2008120130101 ,  G06T2207/2008420130101 ,  G06T2207/3002420130101 ,  G06V10/26 ,  G06V10/454 ,  G06V10/25 ,  G06V2201/0320220101 ,  G06V10/82 ,  G06V10/764 ,  G06V10/7788 ,  G06F18/24323

公开(公告)号：EP4418151A1

公开(公告)日：2024-08-21

申请号：EP23156748.8

申请日：2023-02-15

Applicant: Robert Bosch GmbH

Inventor： Huang, Haiwen ,  Zhang, Dan ,  Geiger, Andreas

IPC: G06F18/214 ,  G06V10/25 ,  G06V10/26 ,  G06V10/44 ,  G06V10/764 ,  G06V10/77 ,  G06V10/774 ,  G06V10/82 ,  G06V20/70 ,  G06N3/0455 ,  G06N3/0475 ,  G06N3/0895 ,  G06V20/56

CPC classification number: G06F18/2155 ,  G06V20/70 ,  G06V10/82 ,  G06V10/7753 ,  G06V10/25 ,  G06V10/26 ,  G06V10/454 ,  G06V10/764 ,  G06V10/77 ,  G06N3/0895 ,  G06N3/0475 ,  G06V20/56 ,  G06N3/045 ,  G06N3/094

Abstract: A device and a method for determining a class for at least a part of a digital image, wherein the method comprises providing (202) a classifier for a first class and a second class, determining (206) a digital image comprising an object of the second class in at least the part of the digital image, determining (208) the class for at least the part of the digital image with the classifier, wherein determining (206) the digital image comprises determining the object of the second class with a generative model depending on a label for the first class and/or depending on at least one pixel representing an object of the first class.

公开(公告)号：EP4121894B1

公开(公告)日：2024-08-14

申请号：EP21711260.6

申请日：2021-03-15

IPC: G06V10/26 ,  G06V10/44 ,  G06V10/82 ,  G06V20/10

CPC classification number: G06V10/26 ,  G06V10/454 ,  G06V10/82 ,  G06N3/045 ,  G06V20/188

公开(公告)号：EP4394726A1

公开(公告)日：2024-07-03

申请号：EP22909548.4

申请日：2022-11-04

Applicant: Tencent Technology (Shenzhen) Company Limited

Inventor： ZHAO, Yu ,  LIN, Zhenyu ,  YAO, Jianhua

IPC: G06V10/764 ,  G06V10/26 ,  G06V10/44 ,  G06V10/80 ,  G06V10/82 ,  G06F18/40 ,  G06N3/04

CPC classification number: G06V10/82 ,  G06N3/04 ,  G06N3/08 ,  G06V10/451

Abstract: Embodiments of the present application relate to the technical field of computers, and disclosed are an image classification method and apparatus, a computer device, and a storage medium. The method comprises: obtaining image features of a pathological image to be classified; for each scale in a plurality of scales, extracting local features corresponding to the scale from the image features; performing splicing processing according to the local features corresponding to each scale to obtain a spliced image feature; and classifying the spliced image feature to obtain a category to which the pathological image belongs. According to the method provided by the embodiments of the present application, local features corresponding to different scales contain different information, so that the finally obtained spliced image feature contains feature information corresponding to different scales, and the feature information of the spliced image feature is enriched; and the category to which the pathological image belongs is determined on the basis of the spliced image feature, so that the accuracy of the category is ensured.