/var/www/htdocs/pustaka-digital/lib/SearchEngine/SearchBiblioEngine.php:688 "Search Engine Debug 🔎 🪲"
Engine Type ⚙️: "SLiMS\SearchEngine\SearchBiblioEngine"
SQL ⚙️: array:2 [ "count" => "select count(sb.biblio_id) from search_biblio as sb where sb.opac_hide=0 and ((match (sb.author) against (:author in boolean mode)))" "query" => "select sb.biblio_id, sb.title, sb.author, sb.topic, sb.image, sb.isbn_issn, sb.publisher, sb.publish_place, sb.publish_year, sb.labels, sb.input_date, sb.edition, sb.collation, sb.series_title, sb.call_number from search_biblio as sb where sb.opac_hide=0 and ((match (sb.author) against (:author in boolean mode))) order by sb.last_update desc limit 10 offset 0" ]
Bind Value ⚒️: array:1 [ ":author" => "'+\"Becker, Stefan\"'" ]
This work addresses the problem of how to capture the dynamics of maneuvering objects for visual tracking. Towards this end, the perspective of recursive Bayesian filters and the perspective of deep learning approaches for state estimation are considered and their functional viewpoints are brought together.