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EP3832341
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EP About this file: EP3832341
| EP3832341 - DEEP NEURAL NETWORK FOR DETECTING OBSTACLE INSTANCES USING RADAR SENSORS IN AUTONOMOUS MACHINE APPLICATIONS [Right-click to bookmark this link] | Status | Examination is in progress Status updated on 24.11.2023 Database last updated on 24.08.2024 | |
| Former | Request for examination was made Status updated on 10.12.2021 | ||
| Former | The application has been published Status updated on 07.05.2021 | Most recent event Tooltip | 15.03.2024 | New entry: Reply to examination report | Applicant(s) | For all designated states NVIDIA Corporation 2788 San Tomas Expressway Santa Clara, CA 95051 / US | [2021/23] | Inventor(s) | 01 /
POPOV, Alexander c/o NVIDIA Corporation 2788 San Tomas Expressway Santa Clara, CA 95051 / US | 02 /
SMOLYANSKIY, Nikolai c/o NVIDIA Corporation 2788 San Tomas Expressway Santa Clara, CA 95051 / US | 03 /
OLDJA, Ryan c/o NVIDIA Corporation 2788 San Tomas Expressway Santa Clara, CA 95051 / US | 04 /
MURRAY, Shane c/o NVIDIA Corporation 2788 San Tomas Expressway Santa Clara, CA 95051 / US | 05 /
WEKEL, Tilman c/o NVIDIA Corporation 2788 San Tomas Expressway Santa Clara, CA 95051 / US | 06 /
NISTER, David c/o NVIDIA Corporation 2788 San Tomas Expressway Santa Clara, CA 95051 / US | 07 /
PEHSERL, Joachim c/o NVIDIA Corporation 2788 San Tomas Expressway Santa Clara, CA 95051 / US | 08 /
BHARGAVA, Ruchi c/o NVIDIA Corporation 2788 San Tomas Expressway Santa Clara, CA 95051 / US | 09 /
OH, Sangmin c/o NVIDIA Corporation 2788 San Tomas Expressway Santa Clara, CA 95051 / US | [2021/23] | Representative(s) | Kraus & Lederer PartGmbB Thomas-Wimmer-Ring 15 80539 München / DE | [N/P] |
| Former [2021/23] | Kraus & Weisert Patentanwälte PartGmbB Thomas-Wimmer-Ring 15 80539 München / DE | Application number, filing date | 20205868.1 | 05.11.2020 | [2021/23] | Priority number, date | US201962938852P | 21.11.2019 Original published format: US 201962938852 P | US202016836583 | 31.03.2020 Original published format: US202016836583 | US202016836618 | 31.03.2020 Original published format: US202016836618 | [2021/23] | Filing language | EN | Procedural language | EN | Publication | Type: | A1 Application with search report | No.: | EP3832341 | Date: | 09.06.2021 | Language: | EN | [2021/23] | Search report(s) | (Supplementary) European search report - dispatched on: | EP | 10.05.2021 | Classification | IPC: | G01S7/41, G01S7/48, G01S13/86, G01S13/89, G01S13/931, G01S17/931, G01S17/89, G01S7/295, G01S7/40, G01S7/497, G06K9/62, G06K9/00, // G01S13/524 | [2021/23] | CPC: |
G01S7/40 (EP,US);
G06V20/56 (CN);
G01C21/165 (CN);
G01S13/865 (EP);
G01S13/89 (EP);
G01S13/931 (EP,CN);
G01S17/89 (EP);
G01S17/931 (EP,CN);
G01S7/417 (EP);
G01S7/4802 (EP);
G01S7/497 (EP);
G06F18/241 (CN);
G06N3/045 (CN);
G06N3/08 (CN);
G06V10/764 (EP,US);
G06V10/82 (EP,US);
G06V20/58 (EP,US);
G06V20/64 (EP,US);
| Designated contracting states | AL, AT, BE, BG, CH, CY, CZ, DE, DK, EE, ES, FI, FR, GB, GR, HR, HU, IE, IS, IT, LI, LT, LU, LV, MC, MK, MT, NL, NO, PL, PT, RO, RS, SE, SI, SK, SM, TR [2022/02] |
| Former [2021/23] | AL, AT, BE, BG, CH, CY, CZ, DE, DK, EE, ES, FI, FR, GB, GR, HR, HU, IE, IS, IT, LI, LT, LU, LV, MC, MK, MT, NL, NO, PL, PT, RO, RS, SE, SI, SK, SM, TR | Extension states | BA | Not yet paid | ME | Not yet paid | Validation states | KH | Not yet paid | MA | Not yet paid | MD | Not yet paid | TN | Not yet paid | Title | German: | TIEFES NEURONALES NETZWERK ZUR ERKENNUNG VON HINDERNISZUSTÄNDEN MITTELS RADARSENSOREN IN AUTONOMEN MASCHINENANWENDUNGEN | [2021/23] | English: | DEEP NEURAL NETWORK FOR DETECTING OBSTACLE INSTANCES USING RADAR SENSORS IN AUTONOMOUS MACHINE APPLICATIONS | [2021/23] | French: | RÉSEAU NEURONAL PROFOND POUR DÉTECTER DES INSTANCES D'OBSTACLES AU MOYEN DE CAPTEURS RADAR DANS DES APPLICATIONS DE MACHINE AUTONOME | [2021/23] | Examination procedure | 08.12.2021 | Amendment by applicant (claims and/or description) | 08.12.2021 | Examination requested [2022/02] | 08.12.2021 | Date on which the examining division has become responsible | 23.11.2023 | Despatch of a communication from the examining division (Time limit: M04) | 15.03.2024 | Reply to a communication from the examining division | Fees paid | Renewal fee | 22.11.2022 | Renewal fee patent year 03 | 22.11.2023 | Renewal fee patent year 04 |
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| Responsibility for the accuracy, completeness or quality of the data displayed under the link provided lies entirely with the Unified Patent Court. | Documents cited: | Search | [Y]US2018314253 (MERCEP LJUBO [DE], et al) [Y] 3,5,6,11,12,14,15,18 * paragraphs [0023] - [0025] - [ 0038] , [ 0039] , [0 43] , [0 48] - [0052] - [0 59] , [0 69] , [0 70] , [ 0083]; figures 1, 2A,2B,5A,5B *; | [XYI]EP3525000 (BAYERISCHE MOTOREN WERKE AG [DE]) [X] 1,2,7-10,16,17,19 * the whole document * [Y] 3-6,11-15,18 [I] 1,2,4,7-10,12,13,16,17,19; | [Y] - NEZHADARYA EHSAN ET AL, "BoxNet: A Deep Learning Method for 2D Bounding Box Estimation from Bird's-Eye View Point Cloud", 2019 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV), IEEE, (20190609), doi:10.1109/IVS.2019.8814058, pages 1557 - 1564, XP033606092 [Y] 4,12,13 * page 1558 - page 1560 * DOI: http://dx.doi.org/10.1109/IVS.2019.8814058 |