{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/124593"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/124593","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Fusing multimodal neural networks: a study on sleep classification and sound event localization and detection","abstract":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2026-05-01","abstract_html":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2026-05-01","abstract_has_math":false,"creators":["Chang, Kai Chieh"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Electrical & Computer Engr","degree_department":null,"school":null,"contributors":["Hasegawa-Johnson, Mark"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2024,"date_issued":"2024-05","date_published":"2024-05","updated_at":"2026-07-22T22:25:02Z","subjects":["Multimodal","Machine Learning"],"languages":["en","eng"],"rights":["Copyright 2024 Kai Chieh Chang"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/124593","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Hasegawa-Johnson, Mark"]},{"key":"dc:creator","label":"Author","values":["Chang, Kai Chieh"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2024-05","2024-04-30"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical & Computer Engr"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Multimodal","Machine Learning"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2024 Kai Chieh Chang"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/124593"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2026-05-01","The student, Kai Chieh Chang, accepted the attached license on 2024-04-29 at 13:15.","The student, Kai Chieh Chang, submitted this Thesis for approval on 2024-04-29 at 13:22.","This Thesis was approved for publication on 2024-04-30 at 15:23.","DSpace SAF Submission Ingestion Package generated from Vireo submission #20692 on 2024-09-16 at 00:44:51","This is an explorative study of multimodal large-scale transformer networks. The thesis explores methods to pretrain and fuse multiple large-scale transformer networks each responsible for a modality, in order to improve their performance on different tasks. Specifically, we first dive into the task of infant sleep classification using audio, electrocardiogram (ECG), and inertial measurement unit (IMU). We explore various pretraining and finetuning schemes, as well as different fusion techniques. We also assess the effectiveness of fusion by cross-attention with sound event localization and detection (SELD), a multichannel machine learning task with multiple outputs. We show that this multimodal network structure is generic enough to work in various settings."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Fusing multimodal neural networks: a study on sleep classification and sound event localization and detection"]}]}],"canonical_facts":{"dc:contributor":["Hasegawa-Johnson, Mark"],"dc:creator":["Chang, Kai Chieh"],"dc:date":["2024-05","2024-04-30"],"dc:description":["Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2026-05-01","The student, Kai Chieh Chang, accepted the attached license on 2024-04-29 at 13:15.","The student, Kai Chieh Chang, submitted this Thesis for approval on 2024-04-29 at 13:22.","This Thesis was approved for publication on 2024-04-30 at 15:23.","DSpace SAF Submission Ingestion Package generated from Vireo submission #20692 on 2024-09-16 at 00:44:51","This is an explorative study of multimodal large-scale transformer networks. The thesis explores methods to pretrain and fuse multiple large-scale transformer networks each responsible for a modality, in order to improve their performance on different tasks. Specifically, we first dive into the task of infant sleep classification using audio, electrocardiogram (ECG), and inertial measurement unit (IMU). We explore various pretraining and finetuning schemes, as well as different fusion techniques. We also assess the effectiveness of fusion by cross-attention with sound event localization and detection (SELD), a multichannel machine learning task with multiple outputs. We show that this multimodal network structure is generic enough to work in various settings."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/124593"],"dc:language":["en","eng"],"dc:rights":["Copyright 2024 Kai Chieh Chang"],"dc:subject":["Multimodal","Machine Learning"],"dc:title":["Fusing multimodal neural networks: a study on sleep classification and sound event localization and detection"],"dc:type":["text"],"thesis:degree_discipline":["Electrical & Computer Engr"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:02Z"}