no code implementations • 17 Jul 2022 • Hanadi Hassen Mohammed, Junaid Malik, Somaya Al-Madeed, Serkan Kiranyaz
With their heterogeneous network structure incorporating non-linear neurons, Operational Neural Networks (ONNs) have recently been proposed to address this drawback.
2 code implementations • 29 Jan 2022 • Serkan Kiranyaz, Ozer Can Devecioglu, Turker Ince, Junaid Malik, Muhammad Chowdhury, Tahir Hamid, Rashid Mazhar, Amith Khandakar, Anas Tahir, Tawsifur Rahman, Moncef Gabbouj
Usually, a set of such artifacts occur on the same ECG signal with varying severity and duration, and this makes an accurate diagnosis by machines or medical doctors extremely difficult.
no code implementations • 29 Nov 2021 • Junaid Malik, Serkan Kiranyaz, Moncef Gabbouj
As the integration of non-local information is known to benefit denoising, in this work we investigate the use of super neurons for both synthetic and real-world image denoising.
1 code implementation • 30 Sep 2021 • Moncef Gabbouj, Serkan Kiranyaz, Junaid Malik, Muhammad Uzair Zahid, Turker Ince, Muhammad Chowdhury, Amith Khandakar, Anas Tahir
Although numerous R-peak detectors have been proposed in the literature, their robustness and performance levels may significantly deteriorate in low-quality and noisy signals acquired from mobile electrocardiogram (ECG) sensors, such as Holter monitors.
no code implementations • 30 Sep 2021 • Junaid Malik, Ozer Can Devecioglu, Serkan Kiranyaz, Turker Ince, Moncef Gabbouj
Despite the proliferation of numerous deep learning methods proposed for generic ECG classification and arrhythmia detection, compact systems with the real-time ability and high accuracy for classifying patient-specific ECG are still few.
no code implementations • 30 Sep 2021 • Turker Ince, Junaid Malik, Ozer Can Devecioglu, Serkan Kiranyaz, Onur Avci, Levent Eren, Moncef Gabbouj
Preventive maintenance of modern electric rotating machinery (RM) is critical for ensuring reliable operation, preventing unpredicted breakdowns and avoiding costly repairs.
no code implementations • 28 Sep 2021 • Ozer Can Devecioglu, Junaid Malik, Turker Ince, Serkan Kiranyaz, Eray Atalay, Moncef Gabbouj
Glaucoma leads to permanent vision disability by damaging the optical nerve that transmits visual images to the brain.
no code implementations • 3 Aug 2021 • Serkan Kiranyaz, Junaid Malik, Mehmet Yamac, Mert Duman, Ilke Adalioglu, Esin Guldogan, Turker Ince, Moncef Gabbouj
In this article, we present superior (generative) neuron models (or super neurons in short) that allow random or learnable kernel shifts and thus can increase the receptive field size of each connection.
no code implementations • 31 May 2021 • Onur Keleş, A. Murat Tekalp, Junaid Malik, Serkan Kiranyaz
It has become a standard practice to use the convolutional networks (ConvNet) with RELU non-linearity in image restoration and super-resolution (SR).
no code implementations • 25 May 2021 • M. Akin Yilmaz, Onur Keleş, Hilal Güven, A. Murat Tekalp, Junaid Malik, Serkan Kiranyaz
In end-to-end optimized learned image compression, it is standard practice to use a convolutional variational autoencoder with generalized divisive normalization (GDN) to transform images into a latent space.
no code implementations • 4 Mar 2021 • Junaid Malik, Serkan Kiranyaz, Mehmet Yamac, Moncef Gabbouj
Despite their recent success on image denoising, the need for deep and complex architectures still hinders the practical usage of CNNs.
1 code implementation • 4 Mar 2021 • Junaid Malik, Serkan Kiranyaz, Mehmet Yamac, Esin Guldogan, Moncef Gabbouj
Real-world blind denoising poses a unique image restoration challenge due to the non-deterministic nature of the underlying noise distribution.
no code implementations • 23 Nov 2020 • Mohammad Soltanian, Junaid Malik, Jenni Raitoharju, Alexandros Iosifidis, Serkan Kiranyaz, Moncef Gabbouj
Automatic classification of speech commands has revolutionized human computer interactions in robotic applications.
no code implementations • 1 Sep 2020 • Junaid Malik, Serkan Kiranyaz, Moncef Gabbouj
Convolutional Neural Networks (CNNs) have recently become a favored technique for image denoising due to its adaptive learning ability, especially with a deep configuration.
no code implementations • 29 Aug 2020 • Junaid Malik, Serkan Kiranyaz, Moncef Gabbouj
Discriminative learning based on convolutional neural networks (CNNs) aims to perform image restoration by learning from training examples of noisy-clean image pairs.
no code implementations • 21 Aug 2020 • Serkan Kiranyaz, Junaid Malik, Habib Ben Abdallah, Turker Ince, Alexandros Iosifidis, Moncef Gabbouj
As a heterogenous network model, ONNs are based on a generalized neuron model that can encapsulate any set of non-linear operators to boost diversity and to learn highly complex and multi-modal functions or spaces with minimal network complexity and training data.
no code implementations • 11 Aug 2020 • Serkan Kiranyaz, Aysen Degerli, Tahir Hamid, Rashid Mazhar, Rayyan Ahmed, Rayaan Abouhasera, Morteza Zabihi, Junaid Malik, Ridha Hamila, Moncef Gabbouj
It further enables medical experts to gain an enhanced visualization capability of echo images through color-coded segments along with their "maximum motion displacement" plots helping them to better assess wall motion and LV Ejection-Fraction (LVEF).
1 code implementation • 3 Jun 2020 • Junaid Malik, Serkan Kiranyaz, Moncef Gabbouj
Operational Neural Networks (ONNs) have recently been proposed as a special class of artificial neural networks for grid structured data.
2 code implementations • 24 Apr 2020 • Serkan Kiranyaz, Junaid Malik, Habib Ben Abdallah, Turker Ince, Alexandros Iosifidis, Moncef Gabbouj
However, Greedy Iterative Search (GIS) method, which is the search method used to find optimal operators in ONNs takes many training sessions to find a single operator set per layer.
no code implementations • 9 Apr 2019 • Junaid Malik, Serkan Kiranyaz, Riyadh Al-Raoush, Olivier Monga, Patricia Garnier, Sebti Foufou, Abdelaziz Bouras, Alexandros Iosifidis, Moncef Gabbouj, Philippe C. Baveye
Binary segmentation of volumetric images of porous media is a crucial step towards gaining a deeper understanding of the factors governing biogeochemical processes at minute scales.
no code implementations • 27 Mar 2019 • Junaid Malik, Serkan Kiranyaz, Suchitra Kunhoth, Turker Ince, Somaya Al-Maadeed, Ridha Hamila, Moncef Gabbouj
Moreover, we conduct quantitative comparative evaluations among the traditional methods, transfer learning-based methods and the proposed adaptive approach for the particular task of cancer detection and identification from scarce and low-resolution histology images.