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ORCIDStefan Holban
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- affiliation: Politehnica University of Timisoara, Romania
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2020 – today
- 2022
[c27]Marina Adriana Mercioni, Stefan Holban:
Weather Forecasting Modeling Using Soft-Clipping Swish Activation Function. SACI 2022: 99-104- 2021
- [c26]Marina Adriana Mercioni, Stefan Holban:
Soft Clipping Mish - A Novel Activation Function for Deep Learning. ICICT 2021: 13-17 - [c25]Marina Adriana Mercioni, Stefan Holban:
Developing Novel Activation Functions in Time Series Anomaly Detection with LSTM Autoencoder. SACI 2021: 73-78 - [c24]Marina Adriana Mercioni, Stefan Holban:
Soft-Clipping Swish: A Novel Activation Function for Deep Learning. SACI 2021: 225-230 - 2020
- [c23]Marina Adriana Mercioni, Angel Marcel Tat, Stefan Holban:
Improving the Accuracy of Deep Neural Networks Through Developing New Activation Functions. ICCP 2020: 385-391 - [c22]Miruna D. Ciulu, Stefan Holban, Diana Lungeanu
:
Hierarchical Clustering for Image Classification in Dermatology: Towards Mobile Deploying. MIE 2020: 1303-1304
2010 – 2019
- 2019
- [c21]Mohamed Lafif Tej, Stefan Holban:
Determining Optimal Multi-layer Perceptron Structure Using Linear Regression. BIS (1) 2019: 232-246 - [c20]Marina Adriana Mercioni, Stefan Holban:
A Survey of Distance Metrics in Clustering Data Mining Techniques. ICGSP 2019: 44-47 - 2018
- [c19]Mohamed Lafif Tej, Stefan Holban:
Comparative Study of Clustering Distance Measures to Determine Neural Network Architectures. SACI 2018: 189-194 - [c18]Marina Adriana Mercioni, Stefan Holban:
The Recognition of the Architectural Style Using Data Mining Techniques. SACI 2018: 331-338 - 2017
- [j7]Nicolae Teodor Melita, Stefan Holban:
dGAselID: An R Package for Selecting a Variable Number of Features in High Dimensional Data. R J. 9(2): 18 (2017) - 2016
- [j6]Andrei Lihu, Stefan Holban:
A review of ensemble methods for de novo motif discovery in ChIP-Seq data. Briefings Bioinform. 17(4): 731 (2016) - [c17]Nicolae Teodor Melita, Stefan Holban:
An incomplete dominance genetic algorithm approach to microarray data analysis. ICCP 2016: 147-151 - 2015
- [j5]Andrei Lihu, Stefan Holban:
A review of ensemble methods for de novo motif discovery in ChIP-Seq data. Briefings Bioinform. 16(6): 964-973 (2015) - [j4]Andrei Lihu, Stefan Holban:
De novo Motif Prediction using the Fireworks Algorithm. Int. J. Swarm Intell. Res. 6(3): 24-40 (2015) - [c16]Raul Robu, Cristian Vasar, Nicolae Robu, Stefan Holban:
A study on Ant Miner parameters. IISA 2015: 1-11 - [c15]Mirela Frandes, Bogdan Timar, Alexandra Tole, Stefan Holban, Diana Lungeanu:
Mobile Technology Support for Clinical Decision in Diabetic Keto-Acidosis Emergency. MIE 2015: 316-320 - [c14]Radu Andrei Stefan, Ildiko-Angelica Szoke, Stefan Holban:
Hierarchical clustering techniques and classification applied in Content Based Image Retrieval (CBIR). SACI 2015: 147-152 - [c13]Andrei Lihu, Stefan Holban:
The influence of the background model on DNA motif prediction: An assessment for zinc finger transcription factor ZFX. SACI 2015: 295-299 - 2014
- [c12]Cristina Stolojescu-Crisan, Stefan Holban:
An Interactive X-Ray Image Segmentation Technique for Bone Extraction. IWBBIO 2014: 1164-1171 - [c11]Cosmin Cernazanu-Glavan, Diana Lungeanu, Stefan Holban:
Mobile data acquisition towards contextual risk assessment for better disease management in diabetes. SACI 2014: 337-341 - 2013
- [j3]Andrei Lihu, Stefan Holban, Oana-Andreea Lihu:
Particle Swarm Optimization with Disagreements on Stagnation. Trans. Comput. Collect. Intell. 12: 171-190 (2013) - [c10]I. M. Haragos, Stefan Holban, Cosmin Cernazanu-Glavan:
A model to estimate the throughput value for a transport network. SACI 2013: 269-273 - 2012
- [j2]Andrei Lihu, Stefan Holban, Oana-Andreea Popescu:
Real-valued genetic algorithms with disagreements. Memetic Comput. 4(4): 317-325 (2012) - 2011
- [c9]Andrei Lihu, Stefan Holban:
Real-Valued Genetic Algorithms with Disagreements. NICSO 2011: 333-346 - [c8]Natalia Tatar, Stefan Holban:
Introducing Bee Colony Algorithm for Hexxagon game. SACI 2011: 117-121 - [c7]Andrei Lihu, Stefan Holban:
A study on the minimal number of particles for a simplified particle swarm optimization algorithm. SACI 2011: 299-303 - [c6]Andrei Lihu, Stefan Holban:
Particle Swarm Optimization with Disagreements. ICSI (1) 2011: 46-55
2000 – 2009
- 2009
- [c5]Cosmin Cernazanu-Glavan, Stefan Holban:
A Model for Determining the Number of Negative Examples used in Training a MLP. SCSS 2009: 537-542 - [c4]Andrei Lihu, Stefan Holban:
Top five most promising algorithms in scheduling. SACI 2009: 397-404 - 2008
- [c3]Diana Lungeanu, Daniela Zaharie, Stefan Holban, Elena Bernad, Maria Bari, Rodica Noaghiu:
Exploratory Analysis of Medical Coding Practices: the Relevance of Reported Data Quality in Obstetrics-Gynaecology. MIE 2008: 839-844 - 2007
- [c2]Daniela Zaharie, Stefan Holban, Diana Lungeanu, Dan Navolan:
A Computational Intelligence Approach for Ranking Risk Factors in Preterm Birth. SACI 2007: 135-140
1990 – 1999
- 1998
- [c1]Daniela Crivianu-Gaita, F. Miclea, A. Gaspar, Stefan Holban, Gabriel-Miro Muntean:
Prostate ultrasound images processing. Bildverarbeitung für die Medizin 1998
1980 – 1989
- 1986
- [j1]Alexandru T. Balaban, Romul Vancea, Ioan Motoc, Stefan Holban:
Chemical graphs, 43. FORTRAN IV program for computing the numbers of general cubic graphs on p vertices. J. Chem. Inf. Comput. Sci. 26(2): 72-76 (1986)
Coauthor Index
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