no code implementations • 20 Apr 2022 • Şeymanur Aktı, Marwa Qaraqe, Hazim Kemal Ekenel
With the model achieving 94% accuracy on 23 food classes, the developed mobile application has potential to serve the visually impaired in automatic food recognition via images.
1 code implementation • 16 Nov 2021 • Şeymanur Aktı, Ferda Ofli, Muhammad Imran, Hazim Kemal Ekenel
We also propose a new dataset, named Social Media Fight Images (SMFI), comprising real-world images of fight actions.
1 code implementation • 16 Sep 2021 • Şeymanur Aktı, Doğay Kamar, Özgür Anıl Özlü, Ihsan Soydemir, Muhammet Akcan, Abdullah Kul, Islem Rekik
The competing teams developed their ML pipelines with a combination of data pre-processing, dimensionality reduction, and learning methods.
1 code implementation • 9 Dec 2020 • Fabio Valerio Massoli, Fabrizio Falchi, Alperen Kantarcı, Şeymanur Aktı, Hazim Kemal Ekenel, Giuseppe Amato
Indeed, differently from commonly used approaches that consider a neural network as a single computational block, i. e., using the output of the last layer only, MOCCA explicitly leverages the multi-layer structure of deep architectures.
Ranked #80 on Anomaly Detection on MVTec AD
1 code implementation • 11 Feb 2020 • Şeymanur Aktı, Gözde Ayşe Tataroğlu, Hazim Kemal Ekenel
This dataset is made publicly available.