“Franck has proved to be a smart and fast adaptative member of our team. During the time we worked together we had to face many challenges keeping innovation and production environments and he was always working tirelessly. His knowledge of machine learning gave us the opportunity to be at the state of the art in the field. I would recommend him for any position and wish I can work with him again.”
Middlesbrough, England, United Kingdom
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About
Activity
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“Oof! What did I even do this week?!” ...Meetings?!👇🏼 As engineers we tend to focus on how much code we wrote, and how many Jira tickets we moved…
“Oof! What did I even do this week?!” ...Meetings?!👇🏼 As engineers we tend to focus on how much code we wrote, and how many Jira tickets we moved…
Liked by Franck FOTSO
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C’est en regardant ma défunte mère se réveiller chaque jour à 04:00 du matin pour aller chercher du pain 🥖 avec un bassin sur sa tête comme ces…
C’est en regardant ma défunte mère se réveiller chaque jour à 04:00 du matin pour aller chercher du pain 🥖 avec un bassin sur sa tête comme ces…
Liked by Franck FOTSO
Experience & Education
Licenses & Certifications
Publications
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Region-based Deep Hashing for Multi-Instance Aware Image Retrieval
IEEE
This paper introduces an instance-aware hashing approach for large-scale multi-label image retrieval. The proposed method relies on the assumption that a more accurate object bounds lead to a better hashing of instance features. From this assumption, we design a unified deep neural network which simultaneously learns object locations, classes, and hashing functions to build efficient binary codes. Region-DH is designed in the way to have a high interest in each found object and build compact…
This paper introduces an instance-aware hashing approach for large-scale multi-label image retrieval. The proposed method relies on the assumption that a more accurate object bounds lead to a better hashing of instance features. From this assumption, we design a unified deep neural network which simultaneously learns object locations, classes, and hashing functions to build efficient binary codes. Region-DH is designed in the way to have a high interest in each found object and build compact binary codes which involve more foreground patterns. Region-DH is flexible and can be improved with existing deep neural networks (as backbone) or more complex object detectors. Many experiments performed on benchmark datasets show the effectiveness and robustness of Region-DH regarding the state-of-the-art hashing methods.
Other authorsSee publication
Languages
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French
Native or bilingual proficiency
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English
Full professional proficiency
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Graduating, once again! PGCLTHE award by the Teesside University and Fellowship of the Higher Education Academy (FHEA) by AdvanceHE #Convocation…
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#KTP #digitaltransformation project video. Fantastic project and great to work with Pedram Salahshouri Sonal Sarvaiya Franck FOTSO Barry Hebbron…
#KTP #digitaltransformation project video. Fantastic project and great to work with Pedram Salahshouri Sonal Sarvaiya Franck FOTSO Barry Hebbron…
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Great presentation by Binh Nguyen on the work he has been doing embedding AI into Raven Controls to enhance public safety. Really enjoyed all the…
Great presentation by Binh Nguyen on the work he has been doing embedding AI into Raven Controls to enhance public safety. Really enjoyed all the…
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