David Robert Vincent

Array ( [id] => 16193157 [patent_doc_number] => 20200234006 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2020-07-23 [patent_title] => PERFORMING CHEMICAL TEXTUAL ANALYSIS [patent_app_type] => utility [patent_app_number] => 16/842587 [patent_app_country] => US [patent_app_date] => 2020-04-07 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 7910 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -17 [patent_words_short_claim] => 49 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16842587 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 16659763 [patent_doc_number] => 20210056400 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2021-02-25 [patent_title] => Dataflow Triggered Tasks for Accelerated Deep Learning [patent_app_type] => utility [patent_app_number] => 16/840111 [patent_app_country] => US [patent_app_date] => 2020-04-03 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 62890 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -17 [patent_words_short_claim] => 2 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16840111 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 16179477 [patent_doc_number] => 20200226445 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2020-07-16 [patent_title] => IMPLEMENTING NEURAL NETWORKS IN FIXED POINT ARITHMETIC COMPUTING SYSTEMS [patent_app_type] => utility [patent_app_number] => 16/830922 [patent_app_country] => US [patent_app_date] => 2020-03-26 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 5154 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -17 [patent_words_short_claim] => 2 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16830922 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 17069796 [patent_doc_number] => 20210272013 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2021-09-02 [patent_title] => CONCEPT MODELING SYSTEM [patent_app_type] => utility [patent_app_number] => 16/803777 [patent_app_country] => US [patent_app_date] => 2020-02-27 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 13287 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -39 [patent_words_short_claim] => 181 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16803777 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 19398969 [patent_doc_number] => 12073341 [patent_country] => US [patent_kind] => B2 [patent_issue_date] => 2024-08-27 [patent_title] => Proactive spatiotemporal resource allocation and predictive visual analytics system [patent_app_type] => utility [patent_app_number] => 16/792785 [patent_app_country] => US [patent_app_date] => 2020-02-17 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 13 [patent_figures_cnt] => 13 [patent_no_of_words] => 10144 [patent_no_of_claims] => 29 [patent_no_of_ind_claims] => 2 [patent_words_short_claim] => 152 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => patent [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16792785 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 16378531 [patent_doc_number] => 20200327373 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2020-10-15 [patent_title] => MACHINE LEARNING BASED EXTRACTION OF PARTITION OBJECTS FROM ELECTRONIC DOCUMENTS [patent_app_type] => utility [patent_app_number] => 16/790945 [patent_app_country] => US [patent_app_date] => 2020-02-14 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 8992 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -17 [patent_words_short_claim] => 189 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16790945 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 16019025 [patent_doc_number] => 20200184356 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2020-06-11 [patent_title] => Auxiliary Analysis System Using Expert Information and Method Thereof [patent_app_type] => utility [patent_app_number] => 16/789377 [patent_app_country] => US [patent_app_date] => 2020-02-12 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 8158 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -15 [patent_words_short_claim] => 485 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16789377 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 15999065 [patent_doc_number] => 20200175403 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2020-06-04 [patent_title] => SYSTEMS AND METHODS FOR EXPEDITING RULE-BASED DATA PROCESSING [patent_app_type] => utility [patent_app_number] => 16/782611 [patent_app_country] => US [patent_app_date] => 2020-02-05 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 15574 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -17 [patent_words_short_claim] => 186 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16782611 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 15937181 [patent_doc_number] => 20200160224 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2020-05-21 [patent_title] => MACHINE LEARNING APPROACH FOR QUERY RESOLUTION VIA A DYNAMIC DETERMINATION AND ALLOCATION OF EXPERT RESOURCES [patent_app_type] => utility [patent_app_number] => 16/748271 [patent_app_country] => US [patent_app_date] => 2020-01-21 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 17134 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -18 [patent_words_short_claim] => 368 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16748271 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 16738130 [patent_doc_number] => 10963786 [patent_country] => US [patent_kind] => B1 [patent_issue_date] => 2021-03-30 [patent_title] => Establishing a trained machine learning classifier in a blockchain network [patent_app_type] => utility [patent_app_number] => 16/740350 [patent_app_country] => US [patent_app_date] => 2020-01-10 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 41 [patent_figures_cnt] => 41 [patent_no_of_words] => 27711 [patent_no_of_claims] => 25 [patent_no_of_ind_claims] => 9 [patent_words_short_claim] => 198 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => patent [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16740350 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 16943374 [patent_doc_number] => 11055621 [patent_country] => US [patent_kind] => B2 [patent_issue_date] => 2021-07-06 [patent_title] => Methods and apparatus for determining whether a media presentation device is in an on state or an off state [patent_app_type] => utility [patent_app_number] => 16/734067 [patent_app_country] => US [patent_app_date] => 2020-01-03 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 24 [patent_figures_cnt] => 26 [patent_no_of_words] => 19010 [patent_no_of_claims] => 20 [patent_no_of_ind_claims] => 3 [patent_words_short_claim] => 105 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => patent [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16734067 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 16943374 [patent_doc_number] => 11055621 [patent_country] => US [patent_kind] => B2 [patent_issue_date] => 2021-07-06 [patent_title] => Methods and apparatus for determining whether a media presentation device is in an on state or an off state [patent_app_type] => utility [patent_app_number] => 16/734067 [patent_app_country] => US [patent_app_date] => 2020-01-03 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 24 [patent_figures_cnt] => 26 [patent_no_of_words] => 19010 [patent_no_of_claims] => 20 [patent_no_of_ind_claims] => 3 [patent_words_short_claim] => 105 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => patent [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16734067 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 15838375 [patent_doc_number] => 20200134470 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2020-04-30 [patent_title] => COMPRESSED RECURRENT NEURAL NETWORK MODELS [patent_app_type] => utility [patent_app_number] => 16/726119 [patent_app_country] => US [patent_app_date] => 2019-12-23 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 5758 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -16 [patent_words_short_claim] => 2 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16726119 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 15805701 [patent_doc_number] => 20200125993 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2020-04-23 [patent_title] => MACHINE LEARNING APPROACH FOR QUERY RESOLUTION VIA A DYNAMIC DETERMINATION AND ALLOCATION OF EXPERT RESOURCES [patent_app_type] => utility [patent_app_number] => 16/721568 [patent_app_country] => US [patent_app_date] => 2019-12-19 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 17134 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -20 [patent_words_short_claim] => 424 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16721568 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 18766150 [patent_doc_number] => 11816553 [patent_country] => US [patent_kind] => B2 [patent_issue_date] => 2023-11-14 [patent_title] => Output from a recurrent neural network [patent_app_type] => utility [patent_app_number] => 16/710205 [patent_app_country] => US [patent_app_date] => 2019-12-11 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 6 [patent_figures_cnt] => 7 [patent_no_of_words] => 9797 [patent_no_of_claims] => 27 [patent_no_of_ind_claims] => 3 [patent_words_short_claim] => 232 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => patent [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16710205 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 18357096 [patent_doc_number] => 11645500 [patent_country] => US [patent_kind] => B2 [patent_issue_date] => 2023-05-09 [patent_title] => Method and system for enhancing training data and improving performance for neural network models [patent_app_type] => utility [patent_app_number] => 16/702442 [patent_app_country] => US [patent_app_date] => 2019-12-03 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 5 [patent_figures_cnt] => 5 [patent_no_of_words] => 11012 [patent_no_of_claims] => 20 [patent_no_of_ind_claims] => 3 [patent_words_short_claim] => 329 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => patent [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16702442 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 15686381 [patent_doc_number] => 20200097854 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2020-03-26 [patent_title] => MACHINE LEARNING APPROACH FOR QUERY RESOLUTION VIA A DYNAMIC DETERMINATION AND ALLOCATION OF EXPERT RESOURCES [patent_app_type] => utility [patent_app_number] => 16/695881 [patent_app_country] => US [patent_app_date] => 2019-11-26 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 17134 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -19 [patent_words_short_claim] => 316 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16695881 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 15655047 [patent_doc_number] => 20200090054 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2020-03-19 [patent_title] => AUTOMATED CREATION OF SEMANTICALLY-ENRICHED DIAGNOSIS MODELS [patent_app_type] => utility [patent_app_number] => 16/688485 [patent_app_country] => US [patent_app_date] => 2019-11-19 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 4922 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -17 [patent_words_short_claim] => 186 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16688485 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 18446382 [patent_doc_number] => 11681954 [patent_country] => US [patent_kind] => B2 [patent_issue_date] => 2023-06-20 [patent_title] => Parallel decoding using transformer models [patent_app_type] => utility [patent_app_number] => 16/682611 [patent_app_country] => US [patent_app_date] => 2019-11-13 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 5 [patent_figures_cnt] => 5 [patent_no_of_words] => 4989 [patent_no_of_claims] => 18 [patent_no_of_ind_claims] => 3 [patent_words_short_claim] => 247 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => patent [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16682611 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 16811055 [patent_doc_number] => 20210133610 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2021-05-06 [patent_title] => LEARNING MODEL AGNOSTIC MULTILEVEL EXPLANATIONS [patent_app_type] => utility [patent_app_number] => 16/668267 [patent_app_country] => US [patent_app_date] => 2019-10-30 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 10502 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -17 [patent_words_short_claim] => 72 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16668267 [rel_patent_id] =>[rel_patent_doc_number] =>)