23 citations · 70 across the 7 of their papers we have counts for
7 papers
3D Quantum Cuts for Automatic Segmentation of Porous Media in Tomography Images
Junaid Malik, Serkan Kiranyaz, Riyadh Al-Raoush +7
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…
Colorectal cancer diagnosis from histology images: A comparative study
Junaid Malik, Serkan Kiranyaz, Suchitra Kunhoth +4
Computer-aided diagnosis (CAD) based on histopathological imaging has progressed rapidly in recent years with the rise of machine learning based methodologies. Traditional approach…
Data-driven Neural Architecture Learning For Financial Time-series Forecasting
Dat Thanh Tran, Juho Kanniainen, Moncef Gabbouj +1
Forecasting based on financial time-series is a challenging task since most real-world data exhibits nonstationary property and nonlinear dependencies. In addition, different data…
1D Convolutional Neural Network Models for Sleep Arousal Detection
Morteza Zabihi, Ali Bahrami Rad, Serkan Kiranyaz +2
Sleep arousals transition the depth of sleep to a more superficial stage. The occurrence of such events is often considered as a protective mechanism to alert the body of harmful s…
Real-time PCG Anomaly Detection by Adaptive 1D Convolutional Neural Networks
Serkan Kiranyaz, Morteza Zabihi, Ali Bahrami Rad +4
The heart sound signals (Phonocardiogram - PCG) enable the earliest monitoring to detect a potential cardiovascular pathology and have recently become a crucial tool as a diagnosti…
Temporal Logistic Neural Bag-of-Features for Financial Time series Forecasting leveraging Limit Order Book Data
Nikolaos Passalis, Anastasios Tefas, Juho Kanniainen +2
Time series forecasting is a crucial component of many important applications, ranging from forecasting the stock markets to energy load prediction. The high-dimensionality, veloci…