Michalis Savelonas (@aspilos74) header
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Michalis Savelonas

@aspilos74

associate professor, department of computer science and biomedical informatics, university of thessaly, research in computer vision and pattern recognition

 Greece
msavelonas.com/
Joined November 2009
  • Tweets483
  • Following510
  • Followers512
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Photo by Michalis Savelonas (@aspilos74)Photo by Michalis Savelonas (@aspilos74)Photo by Michalis Savelonas (@aspilos74)Photo by Michalis Savelonas (@aspilos74)Photo by Michalis Savelonas (@aspilos74)
Recent work "Guiding symbolic regression with fuzzy cognitive maps: a hybrid framework for discovering interpretable, theory-consistent analytical expressions", is now open-access in Applied Soft Computing (IF: 7.8) sciencedirect.com/science/ar… #MachineLearning #FuzzyCognitiveMap
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Guiding symbolic regression with fuzzy cognitive maps: a hybrid framework for discovering interpretable, theory-consistent analytical expressions, new article in Applied Soft Computing (IF: 6,6) sciencedirect.com/science/ar… #MachineLearning #FuzzyCognitiveMap #SymbolicRegression
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Michalis Savelonas retweeted
Warp Records (@WarpRecords) profile picture
Warp Records
@WarpRecordsApr 14
Image from Warp Records (@WarpRecords)
Image from Warp Records (@WarpRecords)
Image from Warp Records (@WarpRecords)
Image from Warp Records (@WarpRecords)
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Leveraging Unlabeled Scans for NCCT Image Segmentation in Early Stroke Diagnosis: A Semi-Supervised GAN Approach, IEEE BIBE 2025 computer.org/csdl/proceeding… #GAN #Segmentation #Stroke #MedicalImageAnalysis

Leveraging Unlabeled Scans for NCCT Image Segmentation in Early Stroke Diagnosis: A Semi-Supervised...

Ischemic stroke is a time-critical medical emergency where rapid diagnosis is essential for improving patient outcomes. Non-contrast computed tomography (NCCT) serves as the frontline imaging tool,...

computer.org
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Deep Learning-based Knowledge Discovery in Medical Imaging – Collection in Discover Data (Springer). We invite submissions. Deadline extended to: 31 December 2025. Collection description and details in the link: link.springer.com/collection… #biomarkers #deeplearning
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Our editorial article introducing the Research Topic "Advances in Biomedical Image Segmentation and Analysis Using Deep Learning" in Frontiers in Signal Processing,  can be accessed here: frontiersin.org/journals/sig…
Frontiers | Editorial: Advances in biomedical image segmentation and analysis using deep learning

Frontiers | Editorial: Advances in biomedical image segmentation and analysis using deep learning

Over the past decade, advances in deep learning (DL) have significantly transformed the landscape of 12 biomedical image segmentation and analysis. The state...

frontiersin.org
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Deep Learning-based Knowledge Discovery in Medical Imaging – Collection in Discover Data (Springer). We invite submissions. Deadline: 30 June 2025. Collection description and details in the link: lnkd.in/dmdmd2Tj #medicalimageanalysis #federatedlearning #fewshot
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Our new work “TransLevelSet: Integrating Vision Transformers with Level-Sets for Medical Image Segmentation” has been published on Neurocomputing (IF: 6.0) sciencedirect.com/science/ar… #AI #VisionTransformers #ViT #medicalimageanalysis
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Our new work entitled "Self-attention-driven Retrieval of Chest CT Images for COVID-19 Assessment" has been published (open access) on Biomedical Physics & Engineering Express (Institute of Physics - IOP) iopscience.iop.org/article/1…

Self-attention-driven retrieval of chest CT images for COVID-19 assessment

Self-attention-driven retrieval of chest CT images for COVID-19 assessment, Fili, Victoria, Savelonas, Michalis

iopscience.iop.org
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Michalis Savelonas retweeted
Joscha Bach (@Plinz) profile picture
Joscha Bach
@Plinz1 Jan 2022
Replying to @fchollet
The model types in music (aesthetics of sequential auditory signals) are very diverse. Eg Baroque music is usually built around state machines while Jazz is often built on a dynamical system
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Vertebrae, IVD and spinal canal boundary extraction on MRI, utilizing CT-trained active shape models link.springer.com/article/10…
Hybrid Representation of Sensor Data for the Classification of Driving Behaviour mdpi.com/1272024 ##mdpiapplsci via @Applsci
Hybrid Representation of Sensor Data for the Classification of Driving Behaviour

Hybrid Representation of Sensor Data for the Classification of Driving Behaviour

Monitoring driving behaviour is important in controlling driving risk, fuel consumption, and CO2 emissions. Recent advances in machine learning, which include several variants of convolutional neural...

mdpi.com
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Michalis Savelonas retweeted
Konstantinos Vardis (@kvarcg) profile picture
Konstantinos Vardis@kvarcg7 May 2021
"Illumination-driven Light Probe Placement" has received best Poster award in #Eurographics2021 conference :) Source code, video and other info here: github.com/cgaueb/light_prob… @EurographicsC @cgaueb @abasilak
Image from Konstantinos Vardis (@kvarcg)
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Michalis Savelonas retweeted
arXiv Daily (@Arxiv_Daily) profile picture
arXiv Daily
@Arxiv_Daily29 Apr 2021
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges deepai.org/publication/geome… by @mmbronstein et al. #ComputerVision #DataScience

Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges

04/27/21 - The last decade has witnessed an experimental revolution in data science and machine learning, epitomised by deep learning methods...

deepai.org
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PU learning-based recognition of structural elements in architectural floor plans #imageanalysis #floorplans #computervision #patternrecognition #machinelearning link.springer.com/article/10…
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Image #Segmentation based on Determinative Brain Storm Optimization, IEEE SMAP 2020 ieeexplore.ieee.org/document…
Hybrid Time-series Representation for the Classification of Driving Behaviour, IEEE SMAP 2020 ieeexplore.ieee.org/document…
An Image-Based Approach for Classification of Driving Behaviour Using CNNs #NeuralNetworks #automotive link.springer.com/chapter/10…
H-V Shadow Detection Based on Electromagnetism-like Optimization, to be presented at EUSIPCO 2020 eurasip.org/Proceedings/Eusi…
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Classification of Driving Behaviour using Short-term and Long-term Summaries of Sensor Data, IEEE SEEDA-CECNSM ieeexplore.ieee.org/document…
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