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Exploring Sound vs Vibration for Robust Fault Detection on Rotating Machinery
Serkan Kiranyaz, Ozer Can Devecioglu, Amir Alhams +4
Robust and real-time detection of faults on rotating machinery has become an ultimate objective for predictive maintenance in various industries. Vibration-based Deep Learning (DL)…
Improving Unimodal Inference with Multimodal Transformers
Kateryna Chumachenko, Alexandros Iosifidis, Moncef Gabbouj
This paper proposes an approach for improving performance of unimodal models with multimodal training. Our approach involves a multi-branch architecture that incorporates unimodal…
Real-Time Vibration-Based Bearing Fault Diagnosis Under Time-Varying Speed Conditions
Tuomas Jalonen, Mohammad Al-Sa'd, Serkan Kiranyaz +1
Detection of rolling-element bearing faults is crucial for implementing proactive maintenance strategies and for minimizing the economic and operational consequences of unexpected…
Cryptocurrency Portfolio Optimization by Neural Networks
Quoc Minh Nguyen, Dat Thanh Tran, Juho Kanniainen +2
Many cryptocurrency brokers nowadays offer a variety of derivative assets that allow traders to perform hedging or speculation. This paper proposes an effective algorithm based on…
SAF-Net: Self-Attention Fusion Network for Myocardial Infarction Detection using Multi-View Echocardiography
Ilke Adalioglu, Mete Ahishali, Aysen Degerli +2
Myocardial infarction (MI) is a severe case of coronary artery disease (CAD) and ultimately, its detection is substantial to prevent progressive damage to the myocardium. In this s…
Convolutional autoencoder-based multimodal one-class classification
Firas Laakom, Fahad Sohrab, Jenni Raitoharju +2
One-class classification refers to approaches of learning using data from a single class only. In this paper, we propose a deep learning one-class classification method suitable fo…
Operational Support Estimator Networks
Mete Ahishali, Mehmet Yamac, Serkan Kiranyaz +1
In this work, we propose a novel approach called Operational Support Estimator Networks (OSENs) for the support estimation task. Support Estimation (SE) is defined as finding the l…
On Feature Diversity in Energy-based Models
Firas Laakom, Jenni Raitoharju, Alexandros Iosifidis +1
Energy-based learning is a powerful learning paradigm that encapsulates various discriminative and generative approaches. An energy-based model (EBM) is typically formed of inner-m…
Optimum Output Long Short-Term Memory Cell for High-Frequency Trading Forecasting
Adamantios Ntakaris, Moncef Gabbouj, Juho Kanniainen
High-frequency trading requires fast data processing without information lags for precise stock price forecasting. This high-paced stock price forecasting is usually based on vecto…
Sound-to-Vibration Transformation for Sensorless Motor Health Monitoring
Ozer Can Devecioglu, Serkan Kiranyaz, Amer Elhmes +6
Automatic sensor-based detection of motor failures such as bearing faults is crucial for predictive maintenance in various industries. Numerous methodologies have been developed ov…
Hyperspectral Image Analysis with Subspace Learning-based One-Class Classification
Sertac Kilickaya, Mete Ahishali, Fahad Sohrab +2
Hyperspectral image (HSI) classification is an important task in many applications, such as environmental monitoring, medical imaging, and land use/land cover (LULC) classification…
Improved Active Fire Detection using Operational U-Nets
Ozer Can Devecioglu, Mete Ahishali, Fahad Sohrab +2
As a consequence of global warming and climate change, the risk and extent of wildfires have been increasing in many areas worldwide. Warmer temperatures and drier conditions can c…
Operational Neural Networks for Parameter-Efficient Hyperspectral Single-Image Super-Resolution
Alexander Ulrichsen, Paul Murray, Stephen Marshall +4
Hyperspectral Imaging is a crucial tool in remote sensing which captures far more spectral information than standard color images. However, the increase in spectral information com…
Deep Learning for Camera Calibration and Beyond: A Survey
Kang Liao, Lang Nie, Shujuan Huang +5
Camera calibration involves estimating camera parameters to infer geometric features from captured sequences, which is crucial for computer vision and robotics. However, convention…
Real-Time Damage Detection in Fiber Lifting Ropes Using Lightweight Convolutional Neural Networks
Tuomas Jalonen, Mohammad Al-Sa'd, Roope Mellanen +2
The health and safety hazards posed by worn crane lifting ropes mandate periodic inspection for damage. This task is time-consuming, prone to human error, halts operation, and may…
Blind Restoration of Real-World Audio by 1D Operational GANs
Turker Ince, Serkan Kiranyaz, Ozer Can Devecioglu +3
Objective: Despite numerous studies proposed for audio restoration in the literature, most of them focus on an isolated restoration problem such as denoising or dereverberation, ig…
WLD-Reg: A Data-dependent Within-layer Diversity Regularizer
Firas Laakom, Jenni Raitoharju, Alexandros Iosifidis +1
Neural networks are composed of multiple layers arranged in a hierarchical structure jointly trained with a gradient-based optimization, where the errors are back-propagated from t…