Towfiq Elahi

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Array ( [id] => 16585222 [patent_doc_number] => 20210019624 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2021-01-21 [patent_title] => ATTENTION-BASED SEQUENCE TRANSDUCTION NEURAL NETWORKS [patent_app_type] => utility [patent_app_number] => 16/988535 [patent_app_country] => US [patent_app_date] => 2020-08-07 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 8203 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -17 [patent_words_short_claim] => 201 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16988535 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 16745657 [patent_doc_number] => 10970651 [patent_country] => US [patent_kind] => B1 [patent_issue_date] => 2021-04-06 [patent_title] => Analytic system for two-stage interactive graphical model selection [patent_app_type] => utility [patent_app_number] => 16/904698 [patent_app_country] => US [patent_app_date] => 2020-06-18 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 22 [patent_figures_cnt] => 22 [patent_no_of_words] => 16041 [patent_no_of_claims] => 30 [patent_no_of_ind_claims] => 3 [patent_words_short_claim] => 407 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => patent [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16904698 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 16895502 [patent_doc_number] => 11037059 [patent_country] => US [patent_kind] => B2 [patent_issue_date] => 2021-06-15 [patent_title] => Self-supervised back propagation for deep learning [patent_app_type] => utility [patent_app_number] => 16/619904 [patent_app_country] => US [patent_app_date] => 2019-08-23 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 4 [patent_figures_cnt] => 4 [patent_no_of_words] => 6809 [patent_no_of_claims] => 26 [patent_no_of_ind_claims] => 2 [patent_words_short_claim] => 452 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => patent [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16619904 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 16217685 [patent_doc_number] => 10733502 [patent_country] => US [patent_kind] => B2 [patent_issue_date] => 2020-08-04 [patent_title] => Training policy neural networks using path consistency learning [patent_app_type] => utility [patent_app_number] => 16/504934 [patent_app_country] => US [patent_app_date] => 2019-07-08 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 3 [patent_figures_cnt] => 3 [patent_no_of_words] => 9633 [patent_no_of_claims] => 20 [patent_no_of_ind_claims] => 3 [patent_words_short_claim] => 460 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => patent [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16504934 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 16486263 [patent_doc_number] => 20200379868 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2020-12-03 [patent_title] => ANOMALY DETECTION USING DEEP LEARNING MODELS [patent_app_type] => utility [patent_app_number] => 16/428302 [patent_app_country] => US [patent_app_date] => 2019-05-31 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 8614 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -15 [patent_words_short_claim] => 161 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16428302 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 15368239 [patent_doc_number] => 20200019884 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2020-01-16 [patent_title] => BINARY SIGNAL CLASSIFIERS THAT TOLERATE INCORRECT TRAINING DATA [patent_app_type] => utility [patent_app_number] => 16/414584 [patent_app_country] => US [patent_app_date] => 2019-05-16 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 17530 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -15 [patent_words_short_claim] => 242 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16414584 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 16193321 [patent_doc_number] => 20200234170 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2020-07-23 [patent_title] => METHOD FOR CLASSIFYING ECO-GEOLOGICAL ENVIRONMENT TYPES BASED ON COAL RESOURCE EXPLOITATION [patent_app_type] => utility [patent_app_number] => 16/639138 [patent_app_country] => US [patent_app_date] => 2019-01-25 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 6762 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -9 [patent_words_short_claim] => 257 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 16639138 [rel_patent_id] =>[rel_patent_doc_number] =>)

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Array ( [id] => 15091381 [patent_doc_number] => 20190340502 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2019-11-07 [patent_title] => PROCESSING GROUP CONVOLUTION IN NEURAL NETWORK PROCESSOR [patent_app_type] => utility [patent_app_number] => 15/971635 [patent_app_country] => US [patent_app_date] => 2018-05-04 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 8897 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -17 [patent_words_short_claim] => 88 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 15971635 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 15043441 [patent_doc_number] => 20190332725 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2019-10-31 [patent_title] => METHOD AND SYSTEM FOR DESIGNING ELECTRICAL MACHINES USING REINFORCEMENT LEARNING [patent_app_type] => utility [patent_app_number] => 15/920949 [patent_app_country] => US [patent_app_date] => 2018-04-30 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 3929 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -18 [patent_words_short_claim] => 140 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 15920949 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 17288685 [patent_doc_number] => 11205236 [patent_country] => US [patent_kind] => B1 [patent_issue_date] => 2021-12-21 [patent_title] => System and method for facilitating real estate transactions by analyzing user-provided data [patent_app_type] => utility [patent_app_number] => 15/879210 [patent_app_country] => US [patent_app_date] => 2018-01-24 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 11 [patent_figures_cnt] => 11 [patent_no_of_words] => 17514 [patent_no_of_claims] => 20 [patent_no_of_ind_claims] => 3 [patent_words_short_claim] => 323 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => patent [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 15879210 [rel_patent_id] =>[rel_patent_doc_number] =>)

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