GB202403824D0 - RGB-D salient object detection method - Google Patents
RGB-D salient object detection methodInfo
- Publication number
- GB202403824D0 GB202403824D0 GBGB2403824.2A GB202403824A GB202403824D0 GB 202403824 D0 GB202403824 D0 GB 202403824D0 GB 202403824 A GB202403824 A GB 202403824A GB 202403824 D0 GB202403824 D0 GB 202403824D0
- Authority
- GB
- United Kingdom
- Prior art keywords
- rgb
- detection method
- object detection
- salient object
- salient
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000001514 detection method Methods 0.000 title 1
Classifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/46—Descriptors for shape, contour or point-related descriptors, e.g. scale invariant feature transform [SIFT] or bags of words [BoW]; Salient regional features
- G06V10/462—Salient features, e.g. scale invariant feature transforms [SIFT]
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/77—Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
- G06V10/80—Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
- G06V10/806—Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level of extracted features
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/045—Combinations of networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/56—Extraction of image or video features relating to colour
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/764—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
- G06V10/765—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects using rules for classification or partitioning the feature space
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V2201/00—Indexing scheme relating to image or video recognition or understanding
- G06V2201/07—Target detection
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Evolutionary Computation (AREA)
- General Physics & Mathematics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Computing Systems (AREA)
- General Health & Medical Sciences (AREA)
- Software Systems (AREA)
- Artificial Intelligence (AREA)
- Health & Medical Sciences (AREA)
- Multimedia (AREA)
- Medical Informatics (AREA)
- Databases & Information Systems (AREA)
- Biomedical Technology (AREA)
- Life Sciences & Earth Sciences (AREA)
- Biophysics (AREA)
- Computational Linguistics (AREA)
- Data Mining & Analysis (AREA)
- Molecular Biology (AREA)
- General Engineering & Computer Science (AREA)
- Mathematical Physics (AREA)
- Image Analysis (AREA)
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202310450234.5A CN116206133B (en) | 2023-04-25 | 2023-04-25 | RGB-D significance target detection method |
Publications (1)
Publication Number | Publication Date |
---|---|
GB202403824D0 true GB202403824D0 (en) | 2024-05-01 |
Family
ID=86513158
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
GBGB2403824.2A Pending GB202403824D0 (en) | 2023-04-25 | 2024-03-18 | RGB-D salient object detection method |
Country Status (2)
Country | Link |
---|---|
CN (1) | CN116206133B (en) |
GB (1) | GB202403824D0 (en) |
Families Citing this family (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN116935052B (en) * | 2023-07-24 | 2024-03-01 | 北京中科睿途科技有限公司 | Semantic segmentation method and related equipment in intelligent cabin environment |
CN117173394B (en) * | 2023-08-07 | 2024-04-02 | 山东大学 | Weak supervision salient object detection method and system for unmanned aerial vehicle video data |
CN117036891B (en) * | 2023-08-22 | 2024-03-29 | 睿尔曼智能科技(北京)有限公司 | Cross-modal feature fusion-based image recognition method and system |
CN117409214A (en) * | 2023-12-14 | 2024-01-16 | 南开大学 | Saliency target detection method and system based on self-adaptive interaction network |
Family Cites Families (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20120113133A1 (en) * | 2010-11-04 | 2012-05-10 | Shpigelblat Shai | System, device, and method for multiplying multi-dimensional data arrays |
US11734545B2 (en) * | 2017-11-14 | 2023-08-22 | Google Llc | Highly efficient convolutional neural networks |
CN110956094B (en) * | 2019-11-09 | 2023-12-01 | 北京工业大学 | RGB-D multi-mode fusion personnel detection method based on asymmetric double-flow network |
CN111582316B (en) * | 2020-04-10 | 2022-06-28 | 天津大学 | RGB-D significance target detection method |
CN112906770A (en) * | 2021-02-04 | 2021-06-04 | 浙江师范大学 | Cross-modal fusion-based deep clustering method and system |
CN113763422B (en) * | 2021-07-30 | 2023-10-03 | 北京交通大学 | RGB-D image saliency target detection method |
CN113486865B (en) * | 2021-09-03 | 2022-03-11 | 国网江西省电力有限公司电力科学研究院 | Power transmission line suspended foreign object target detection method based on deep learning |
CN113935433B (en) * | 2021-11-02 | 2024-06-14 | 齐齐哈尔大学 | Hyperspectral image classification method based on depth spectrum space inverse residual error network |
CN115410046A (en) * | 2022-09-22 | 2022-11-29 | 河南科技大学 | Skin disease tongue picture classification model based on deep learning, establishing method and application |
CN115908789A (en) * | 2022-12-09 | 2023-04-04 | 大连民族大学 | Cross-modal feature fusion and asymptotic decoding saliency target detection method and device |
-
2023
- 2023-04-25 CN CN202310450234.5A patent/CN116206133B/en active Active
-
2024
- 2024-03-18 GB GBGB2403824.2A patent/GB202403824D0/en active Pending
Also Published As
Publication number | Publication date |
---|---|
CN116206133A (en) | 2023-06-02 |
CN116206133B (en) | 2023-09-05 |
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