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Submissions from 2022

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Survey on Self-supervised Representation Learning Using Image Transformations, Muhammad Ali and Sayed Hashim

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Color Space-based HoVer-Net for Nuclei Instance Segmentation and Classification, Hussam Azzuni, Muhammad Ridzuan, Min Xu, and Mohammad Yaqub

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The Power Of First-Order Smooth Optimization for Black-Box Non-Smooth Problems, Alexander V. Gasnikov., Anton Novitskii, Vasilii Novitskii, Farshed Abdukhakimov, Dmitry Kamzolov, Aleksandr Beznosikov, Martin Takáč, Pavel Dvurechensky, and Bin Gu

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Hyperparameter Optimization for COVID-19 Chest X-Ray Classification, Ibraheem Hamdi, Muhammad Ridzuan, and Mohammad Yaqub

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SubOmiEmbed: Self-supervised representation learning of multi-omics data for cancer type classification, Sayed Hashim, Muhammad Ali, Karthik Nandakumar, and Mohammad Yaqub

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Contrastive Self-Supervised Learning: A Survey on Different Architectures, Adnan Khan, Sarah Al Barri, and Muhammad Arslan Manzoor

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Challenges in COVID-19 Chest X-Ray Classification: Problematic Data or Ineffective Approaches?, Muhammad Ridzuan, Ameera Ali Bawazir, Ivo Gollini Navarrete, Ibrahim Almakky, and Mohammad Yaqub

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Is Contrastive Learning Suitable for Left Ventricular Segmentation in Echocardiographic Images?, Mohamed Saeed, Rand Muhtaseb, and Mohammad Yaqub

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An Ensemble Approach for Patient Prognosis of Head and Neck Tumor Using Multimodal Data, Numan Saeed, Roba Al Majzoub, Ikboljon Sobirov, and Mohammad Yaqub

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Is it Possible to Predict MGMT Promoter Methylation from Brain Tumor MRI Scans using Deep Learning Models?, Numan Saeed, Shahad Hardan, Kudaibergen Abutalip, and Mohammad Yaqub

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TransformNet: Self-supervised representation learning through predicting geometric transformations, Hashim Sayed and Muhammad Ali

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Automatic Segmentation of Head and Neck Tumor: How Powerful Transformers Are?, Ikboljon Sobirov, Otabek Nazarov, Hussain Alasmawi, and Mohammad Yaqub

Submissions from 2021

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Self-supervised learning for fine-grained visual categorization, Muhammad Maaz, Hanoona Abdul Rasheed, and Dhanalaxmi Gaddam

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Multi-modal Transformers Excel at Class-agnostic Object Detection, Muhammad Maaz, Hanoona Bangalath Rasheed, Salman Hameed Khan, Fahad Shahbaz Khan, Rao Muhammad Anwer, and Ming-Hsuan Yang