[\/et_pb_text][et_pb_text content_tablet=”<\/p>\n
Dr. Matthew Johnson-Roberson<\/span><\/h1>\n” content_phone=”<\/p>\n
Dr. Matthew Johnson-Roberson<\/span><\/h1>\n” content_last_edited=”on|tablet” _builder_version=”4.19.0″ text_font=”||||||||” header_font=”Montserrat|700||on|||||” header_text_color=”#ffffff” header_font_size=”60px” header_2_font=”||||||||” background_size=”initial” background_position=”top_left” background_repeat=”repeat” custom_margin=”|||” animation_style=”fade” hover_enabled=”0″ header_font_size_last_edited=”off|desktop” locked=”off” global_colors_info=”{}” sticky_enabled=”0″]<\/p>\n
Dr. Matthew Johnson-Roberson<\/span><\/h1>\n[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ admin_label=”Fullwidth Image” _builder_version=”4.16″ custom_padding=”27px|0px|67px|0px||” global_colors_info=”{}”][et_pb_row _builder_version=”4.16″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” width=”100%” custom_padding=”||5px|||” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text content_tablet=”<\/p>\n
Dr. Johnson-Roberson presents from 12-1pm Eastern on October 26th. To join via Teams, please click here<\/a><\/span><\/span>.<\/h1>\n<\/h3>\nLessons from the Field: Deep Learning and Machine Perception for AUVs<\/h3>\n
<\/span><\/p>\nAbstract<\/strong>: AUVs now deliver vast amounts of sensor data from large unstructured marine environments. In<\/span>\u00a0attempting to process and interpret this data there are many unique challenges in bridging the gap between prerecorded data sets and the field. This talk will present recent work addressing the application of machine<\/span>learning techniques to mobile robotic perception. We will discuss solutions to both mapping, 3d Reconstruction, and grasping and manipulation in underwater contexts. Real field data will guide this process and we will show<\/span>\u00a0results on deployed field robotic vehicles.<\/span><\/p>\nBiography: <\/strong>Matthew Johnson-Roberson is director of the Carnegie Mellon Robotics Institute and a Professor in the School of Computer Science. He received a PhD from the University of Sydney in 2010. He has held prior postdoctoral appointments with the Centre for Autonomous Systems – CAS at KTH Royal Institute of Technology in Stockholm and the Australian Centre for Field Robotics at the University of Sydney. He co-founded Refraction AI, a last-mile autonomous vehicle delivery company. He has worked in robotic perception since the first DARPA grand challenge and his group focuses on enabling robots to better see and understand their environment.<\/span><\/p>\n” content_phone=”<\/p>\n
Dr. Johnson-Roberson presents from 12-1pm Eastern on October 26th. To join via Teams, please click here<\/a><\/span><\/span>.<\/h1>\n<\/h3>\nLessons from the Field: Deep Learning and Machine Perception for AUVs<\/h3>\n
<\/span><\/p>\nAbstract<\/strong>: AUVs now deliver vast amounts of sensor data from large unstructured marine environments. In<\/span>\u00a0attempting to process and interpret this data there are many unique challenges in bridging the gap between prerecorded data sets and the field. This talk will present recent work addressing the application of machine<\/span>learning techniques to mobile robotic perception. We will discuss solutions to both mapping, 3d Reconstruction, and grasping and manipulation in underwater contexts. Real field data will guide this process and we will show<\/span>\u00a0results on deployed field robotic vehicles.<\/span><\/p>\nBiography: <\/strong>Matthew Johnson-Roberson is director of the Carnegie Mellon Robotics Institute and a Professor in the School of Computer Science. He received a PhD from the University of Sydney in 2010. He has held prior postdoctoral appointments with the Centre for Autonomous Systems – CAS at KTH Royal Institute of Technology in Stockholm and the Australian Centre for Field Robotics at the University of Sydney. He co-founded Refraction AI, a last-mile autonomous vehicle delivery company. He has worked in robotic perception since the first DARPA grand challenge and his group focuses on enabling robots to better see and understand their environment.<\/span><\/p>\n” content_last_edited=”on|phone” _builder_version=”4.19.0″ _module_preset=”default” custom_padding=”|20px||20px|false|true” hover_enabled=”0″ global_colors_info=”{}” sticky_enabled=”0″]<\/p>\n
Dr. Johnson-Roberson presents from 12-1pm Eastern on October 26th. To join via Teams, please click here<\/a><\/span><\/span>.<\/h1>\n<\/h3>\nLessons from the Field: Deep Learning and Machine Perception for AUVs<\/h3>\n
![\"\"](\"https:\/\/www.marine.usf.edu\/comit\/wp-content\/uploads\/2022\/03\/mjr-headshot-01-scaled-1-200x300.jpg\")
<\/span><\/p>\nAbstract<\/strong>: AUVs now deliver vast amounts of sensor data from large unstructured marine environments. In<\/span>\u00a0attempting to process and interpret this data there are many unique challenges in bridging the gap between prerecorded data sets and the field. This talk will present recent work addressing the application of machine<\/span>learning techniques to mobile robotic perception. We will discuss solutions to both mapping, 3d Reconstruction, and grasping and manipulation in underwater contexts. Real field data will guide this process and we will show<\/span>\u00a0results on deployed field robotic vehicles.<\/span><\/p>\nBiography: <\/strong>Matthew Johnson-Roberson is director of the Carnegie Mellon Robotics Institute and a Professor in the School of Computer Science. He received a PhD from the University of Sydney in 2010. He has held prior postdoctoral appointments with the Centre for Autonomous Systems – CAS at KTH Royal Institute of Technology in Stockholm and the Australian Centre for Field Robotics at the University of Sydney. He co-founded Refraction AI, a last-mile autonomous vehicle delivery company. He has worked in robotic perception since the first DARPA grand challenge and his group focuses on enabling robots to better see and understand their environment.<\/span><\/p>\n[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.17.4″ _module_preset=”default” global_colors_info=”{}”][et_pb_row _builder_version=”4.17.4″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.17.4″ _module_preset=”default” global_colors_info=”{}”][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":"
Center for Ocean Mapping & Innovative Technologies’ Webinar SeriesDr. Matthew Johnson-RobersonDr. Johnson-Roberson presents from 12-1pm Eastern on October 26th. To join via Teams, please click here. Lessons from the Field: Deep Learning and Machine Perception for AUVs Abstract: AUVs now deliver vast amounts of sensor data from large unstructured marine environments. In\u00a0attempting to process and […]<\/p>\n","protected":false},"author":2,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":"","om_disable_all_campaigns":false,"_exactmetrics_skip_tracking":false,"_exactmetrics_sitenote_active":false,"_exactmetrics_sitenote_note":"","_exactmetrics_sitenote_category":0,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"class_list":["post-2009","page","type-page","status-publish","hentry"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/www.marine.usf.edu\/comit\/wp-json\/wp\/v2\/pages\/2009","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.marine.usf.edu\/comit\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.marine.usf.edu\/comit\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.marine.usf.edu\/comit\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.marine.usf.edu\/comit\/wp-json\/wp\/v2\/comments?post=2009"}],"version-history":[{"count":7,"href":"https:\/\/www.marine.usf.edu\/comit\/wp-json\/wp\/v2\/pages\/2009\/revisions"}],"predecessor-version":[{"id":2053,"href":"https:\/\/www.marine.usf.edu\/comit\/wp-json\/wp\/v2\/pages\/2009\/revisions\/2053"}],"wp:attachment":[{"href":"https:\/\/www.marine.usf.edu\/comit\/wp-json\/wp\/v2\/media?parent=2009"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
” content_last_edited=”on|tablet” _builder_version=”4.19.0″ text_font=”||||||||” header_font=”Montserrat|700||on|||||” header_text_color=”#ffffff” header_font_size=”60px” header_2_font=”||||||||” background_size=”initial” background_position=”top_left” background_repeat=”repeat” custom_margin=”|||” animation_style=”fade” hover_enabled=”0″ header_font_size_last_edited=”off|desktop” locked=”off” global_colors_info=”{}” sticky_enabled=”0″]<\/p>\n
Dr. Matthew Johnson-Roberson<\/span><\/h1>\n[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ admin_label=”Fullwidth Image” _builder_version=”4.16″ custom_padding=”27px|0px|67px|0px||” global_colors_info=”{}”][et_pb_row _builder_version=”4.16″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” width=”100%” custom_padding=”||5px|||” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text content_tablet=”<\/p>\n
Dr. Johnson-Roberson presents from 12-1pm Eastern on October 26th. To join via Teams, please click here<\/a><\/span><\/span>.<\/h1>\n<\/h3>\nLessons from the Field: Deep Learning and Machine Perception for AUVs<\/h3>\n
<\/span><\/p>\nAbstract<\/strong>: AUVs now deliver vast amounts of sensor data from large unstructured marine environments. In<\/span>\u00a0attempting to process and interpret this data there are many unique challenges in bridging the gap between prerecorded data sets and the field. This talk will present recent work addressing the application of machine<\/span>learning techniques to mobile robotic perception. We will discuss solutions to both mapping, 3d Reconstruction, and grasping and manipulation in underwater contexts. Real field data will guide this process and we will show<\/span>\u00a0results on deployed field robotic vehicles.<\/span><\/p>\nBiography: <\/strong>Matthew Johnson-Roberson is director of the Carnegie Mellon Robotics Institute and a Professor in the School of Computer Science. He received a PhD from the University of Sydney in 2010. He has held prior postdoctoral appointments with the Centre for Autonomous Systems – CAS at KTH Royal Institute of Technology in Stockholm and the Australian Centre for Field Robotics at the University of Sydney. He co-founded Refraction AI, a last-mile autonomous vehicle delivery company. He has worked in robotic perception since the first DARPA grand challenge and his group focuses on enabling robots to better see and understand their environment.<\/span><\/p>\n” content_phone=”<\/p>\n
Dr. Johnson-Roberson presents from 12-1pm Eastern on October 26th. To join via Teams, please click here<\/a><\/span><\/span>.<\/h1>\n<\/h3>\nLessons from the Field: Deep Learning and Machine Perception for AUVs<\/h3>\n
<\/span><\/p>\nAbstract<\/strong>: AUVs now deliver vast amounts of sensor data from large unstructured marine environments. In<\/span>\u00a0attempting to process and interpret this data there are many unique challenges in bridging the gap between prerecorded data sets and the field. This talk will present recent work addressing the application of machine<\/span>learning techniques to mobile robotic perception. We will discuss solutions to both mapping, 3d Reconstruction, and grasping and manipulation in underwater contexts. Real field data will guide this process and we will show<\/span>\u00a0results on deployed field robotic vehicles.<\/span><\/p>\nBiography: <\/strong>Matthew Johnson-Roberson is director of the Carnegie Mellon Robotics Institute and a Professor in the School of Computer Science. He received a PhD from the University of Sydney in 2010. He has held prior postdoctoral appointments with the Centre for Autonomous Systems – CAS at KTH Royal Institute of Technology in Stockholm and the Australian Centre for Field Robotics at the University of Sydney. He co-founded Refraction AI, a last-mile autonomous vehicle delivery company. He has worked in robotic perception since the first DARPA grand challenge and his group focuses on enabling robots to better see and understand their environment.<\/span><\/p>\n” content_last_edited=”on|phone” _builder_version=”4.19.0″ _module_preset=”default” custom_padding=”|20px||20px|false|true” hover_enabled=”0″ global_colors_info=”{}” sticky_enabled=”0″]<\/p>\n
Dr. Johnson-Roberson presents from 12-1pm Eastern on October 26th. To join via Teams, please click here<\/a><\/span><\/span>.<\/h1>\n<\/h3>\nLessons from the Field: Deep Learning and Machine Perception for AUVs<\/h3>\n
<\/span><\/p>\nAbstract<\/strong>: AUVs now deliver vast amounts of sensor data from large unstructured marine environments. In<\/span>\u00a0attempting to process and interpret this data there are many unique challenges in bridging the gap between prerecorded data sets and the field. This talk will present recent work addressing the application of machine<\/span>learning techniques to mobile robotic perception. We will discuss solutions to both mapping, 3d Reconstruction, and grasping and manipulation in underwater contexts. Real field data will guide this process and we will show<\/span>\u00a0results on deployed field robotic vehicles.<\/span><\/p>\nBiography: <\/strong>Matthew Johnson-Roberson is director of the Carnegie Mellon Robotics Institute and a Professor in the School of Computer Science. He received a PhD from the University of Sydney in 2010. He has held prior postdoctoral appointments with the Centre for Autonomous Systems – CAS at KTH Royal Institute of Technology in Stockholm and the Australian Centre for Field Robotics at the University of Sydney. He co-founded Refraction AI, a last-mile autonomous vehicle delivery company. He has worked in robotic perception since the first DARPA grand challenge and his group focuses on enabling robots to better see and understand their environment.<\/span><\/p>\n[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.17.4″ _module_preset=”default” global_colors_info=”{}”][et_pb_row _builder_version=”4.17.4″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.17.4″ _module_preset=”default” global_colors_info=”{}”][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":"
Center for Ocean Mapping & Innovative Technologies’ Webinar SeriesDr. Matthew Johnson-RobersonDr. Johnson-Roberson presents from 12-1pm Eastern on October 26th. To join via Teams, please click here. Lessons from the Field: Deep Learning and Machine Perception for AUVs Abstract: AUVs now deliver vast amounts of sensor data from large unstructured marine environments. In\u00a0attempting to process and […]<\/p>\n","protected":false},"author":2,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":"","om_disable_all_campaigns":false,"_exactmetrics_skip_tracking":false,"_exactmetrics_sitenote_active":false,"_exactmetrics_sitenote_note":"","_exactmetrics_sitenote_category":0,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"class_list":["post-2009","page","type-page","status-publish","hentry"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/www.marine.usf.edu\/comit\/wp-json\/wp\/v2\/pages\/2009","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.marine.usf.edu\/comit\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.marine.usf.edu\/comit\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.marine.usf.edu\/comit\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.marine.usf.edu\/comit\/wp-json\/wp\/v2\/comments?post=2009"}],"version-history":[{"count":7,"href":"https:\/\/www.marine.usf.edu\/comit\/wp-json\/wp\/v2\/pages\/2009\/revisions"}],"predecessor-version":[{"id":2053,"href":"https:\/\/www.marine.usf.edu\/comit\/wp-json\/wp\/v2\/pages\/2009\/revisions\/2053"}],"wp:attachment":[{"href":"https:\/\/www.marine.usf.edu\/comit\/wp-json\/wp\/v2\/media?parent=2009"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
<\/h3>\nLessons from the Field: Deep Learning and Machine Perception for AUVs<\/h3>\n
Abstract<\/strong>: AUVs now deliver vast amounts of sensor data from large unstructured marine environments. In<\/span>\u00a0attempting to process and interpret this data there are many unique challenges in bridging the gap between prerecorded data sets and the field. This talk will present recent work addressing the application of machine<\/span>learning techniques to mobile robotic perception. We will discuss solutions to both mapping, 3d Reconstruction, and grasping and manipulation in underwater contexts. Real field data will guide this process and we will show<\/span>\u00a0results on deployed field robotic vehicles.<\/span><\/p>\n Biography: <\/strong>Matthew Johnson-Roberson is director of the Carnegie Mellon Robotics Institute and a Professor in the School of Computer Science. He received a PhD from the University of Sydney in 2010. He has held prior postdoctoral appointments with the Centre for Autonomous Systems – CAS at KTH Royal Institute of Technology in Stockholm and the Australian Centre for Field Robotics at the University of Sydney. He co-founded Refraction AI, a last-mile autonomous vehicle delivery company. He has worked in robotic perception since the first DARPA grand challenge and his group focuses on enabling robots to better see and understand their environment.<\/span><\/p>\n ” content_phone=”<\/p>\n Abstract<\/strong>: AUVs now deliver vast amounts of sensor data from large unstructured marine environments. In<\/span>\u00a0attempting to process and interpret this data there are many unique challenges in bridging the gap between prerecorded data sets and the field. This talk will present recent work addressing the application of machine<\/span>learning techniques to mobile robotic perception. We will discuss solutions to both mapping, 3d Reconstruction, and grasping and manipulation in underwater contexts. Real field data will guide this process and we will show<\/span>\u00a0results on deployed field robotic vehicles.<\/span><\/p>\n Biography: <\/strong>Matthew Johnson-Roberson is director of the Carnegie Mellon Robotics Institute and a Professor in the School of Computer Science. He received a PhD from the University of Sydney in 2010. He has held prior postdoctoral appointments with the Centre for Autonomous Systems – CAS at KTH Royal Institute of Technology in Stockholm and the Australian Centre for Field Robotics at the University of Sydney. He co-founded Refraction AI, a last-mile autonomous vehicle delivery company. He has worked in robotic perception since the first DARPA grand challenge and his group focuses on enabling robots to better see and understand their environment.<\/span><\/p>\n ” content_last_edited=”on|phone” _builder_version=”4.19.0″ _module_preset=”default” custom_padding=”|20px||20px|false|true” hover_enabled=”0″ global_colors_info=”{}” sticky_enabled=”0″]<\/p>\n Abstract<\/strong>: AUVs now deliver vast amounts of sensor data from large unstructured marine environments. In<\/span>\u00a0attempting to process and interpret this data there are many unique challenges in bridging the gap between prerecorded data sets and the field. This talk will present recent work addressing the application of machine<\/span>learning techniques to mobile robotic perception. We will discuss solutions to both mapping, 3d Reconstruction, and grasping and manipulation in underwater contexts. Real field data will guide this process and we will show<\/span>\u00a0results on deployed field robotic vehicles.<\/span><\/p>\n Biography: <\/strong>Matthew Johnson-Roberson is director of the Carnegie Mellon Robotics Institute and a Professor in the School of Computer Science. He received a PhD from the University of Sydney in 2010. He has held prior postdoctoral appointments with the Centre for Autonomous Systems – CAS at KTH Royal Institute of Technology in Stockholm and the Australian Centre for Field Robotics at the University of Sydney. He co-founded Refraction AI, a last-mile autonomous vehicle delivery company. He has worked in robotic perception since the first DARPA grand challenge and his group focuses on enabling robots to better see and understand their environment.<\/span><\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.17.4″ _module_preset=”default” global_colors_info=”{}”][et_pb_row _builder_version=”4.17.4″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.17.4″ _module_preset=”default” global_colors_info=”{}”][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":" Center for Ocean Mapping & Innovative Technologies’ Webinar SeriesDr. Matthew Johnson-RobersonDr. Johnson-Roberson presents from 12-1pm Eastern on October 26th. To join via Teams, please click here. Lessons from the Field: Deep Learning and Machine Perception for AUVs Abstract: AUVs now deliver vast amounts of sensor data from large unstructured marine environments. In\u00a0attempting to process and […]<\/p>\n","protected":false},"author":2,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":"","om_disable_all_campaigns":false,"_exactmetrics_skip_tracking":false,"_exactmetrics_sitenote_active":false,"_exactmetrics_sitenote_note":"","_exactmetrics_sitenote_category":0,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"class_list":["post-2009","page","type-page","status-publish","hentry"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/www.marine.usf.edu\/comit\/wp-json\/wp\/v2\/pages\/2009","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.marine.usf.edu\/comit\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.marine.usf.edu\/comit\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.marine.usf.edu\/comit\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.marine.usf.edu\/comit\/wp-json\/wp\/v2\/comments?post=2009"}],"version-history":[{"count":7,"href":"https:\/\/www.marine.usf.edu\/comit\/wp-json\/wp\/v2\/pages\/2009\/revisions"}],"predecessor-version":[{"id":2053,"href":"https:\/\/www.marine.usf.edu\/comit\/wp-json\/wp\/v2\/pages\/2009\/revisions\/2053"}],"wp:attachment":[{"href":"https:\/\/www.marine.usf.edu\/comit\/wp-json\/wp\/v2\/media?parent=2009"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}<\/span><\/p>\nDr. Johnson-Roberson presents from 12-1pm Eastern on October 26th. To join via Teams, please click here<\/a><\/span><\/span>.<\/h1>\n
<\/h3>\n
Lessons from the Field: Deep Learning and Machine Perception for AUVs<\/h3>\n
<\/span><\/p>\nDr. Johnson-Roberson presents from 12-1pm Eastern on October 26th. To join via Teams, please click here<\/a><\/span><\/span>.<\/h1>\n
<\/h3>\n
Lessons from the Field: Deep Learning and Machine Perception for AUVs<\/h3>\n
<\/span><\/p>\n