Sinan Kalkan

E-mail

skalkan@metu.edu.tr

Department

Department of Computer Engineering

ORCID

0000-0003-0915-5917

Scopus Author ID

23027462100

Web of Science Researcher ID

A-4843-2016

An explainable two-stage machine learning approach for precipitation forecast Senocak, Ali Ulvi Galip; Yılmaz, Mustafa Tuğrul; Kalkan, Sinan; Yücel, İsmail; Amjad, Muhammad (2023-12-01) A common post-processing approach to improve precipitation forecasts is to use machine learning models such as artificial neural networks (more specifically, multi-layer perceptrons) as black-box systems. These models util...
TMO-Det: Deep tone-mapping optimized with and for object detection Koçdemir, İsmail Hakkı; Koz, Alper; Akyuz, Ahmet Oguz; Chalmers, Alan; Alatan, Abdullah Aydın; Kalkan, Sinan (2023-08-01)
Counterfactual Fairness for Facial Expression Recognition Cheong, Jiaee; Kalkan, Sinan; Gunes, Hatice (2023-01-01) Given the increasing prevalence of facial analysis technology, the problem of bias in these tools is becoming an even greater source of concern. Causality has been proposed as a method to address the problem of bias, givin...
Causal Structure Learning of Bias for Fair Affect Recognition Cheong, Jiaee; Kalkan, Sinan; Gunes, Hatice (2023-01-01) The problem of bias in facial affect recognition tools can lead to severe consequences and issues. It has been posited that causality is able to address the gaps induced by the associational nature of traditional machine l...
Useful Daylight Illuminance Prediction Under Data Imbalance in an Urban Context Canli, Ilkim; Kalkan, Sinan; Gürsel Dino, İpek (2023-01-01) Optimal daylight illumination can aid sustainable design by improving occupants’ psychological and physical health, visual and thermal comfort and decreasing electrical lighting energy usage in buildings. However, dense ur...
Towards Causal Replay for Knowledge Rehearsal in Continual Learning Churamani, Nikhil; Cheong, Jiaee; Kalkan, Sinan; Gunes, Hatice (2023-01-01) Given the challenges associated with the real-world deployment of Machine Learning (ML) models, especially towards efficiently integrating novel information on-the-go, both Continual Learning (CL) and Causality have been p...
Vision-based estimation of the number of occupants using video cameras Gürsel Dino, İpek; Kalfaoglu, Esat; Iseri, Orcun Koral; Erdogan, Bilge; Kalkan, Sinan; Alatan, Abdullah Aydın (2022-08-01) Although occupancy information is critical to energy consumption of existing buildings, it still remains to be a major source of uncertainty. For reliable and accurate occupant modeling with minimal uncertainties, capturin...
Does depth estimation help object detection? Cetinkaya, Bedrettin; Kalkan, Sinan; Akbaş, Emre (2022-06-01) Ground-truth depth, when combined with color data, helps improve object detection accuracy over baseline models that only use color. However, estimated depth does not always yield improvements. Many factors affect the perf...
Compiling Open Datasets to Improve Urban Building Energy Models with Occupancy and Layout Data Duran, Ayça; Işeri, Orçun Koral; Akgül, Çağla; Kalkan, Sinan; Gürsel Dino, İpek (2022-04-15) Urban building energy modelling (UBEM) has great potential for assessing the energy performance of the existing building stock and exploring various actions targeting energy efficiency. However, the precision and completen...
Hand-crafted versus learned representations for audio event detection Kucukbay, Selver Ezgi; Yazıcı, Adnan; Kalkan, Sinan (2022-04-01) Audio Event Detection (AED) pertains to identifying the types of events in audio signals. AED is essential for applications requiring decisions based on audio signals, which can be critical, for example, for health, survei...

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