Daniyal Kazempour
Daniyal Kazempour
PhD Student, LMU Munich
Bestätigte E-Mail-Adresse bei dbs.ifi.lmu.de
Titel
Zitiert von
Zitiert von
Jahr
antiSMASH 2.0—a versatile platform for genome mining of secondary metabolite producers
K Blin, MH Medema, D Kazempour, MA Fischbach, R Breitling, E Takano, ...
Nucleic acids research 41 (W1), W204-W212, 2013
8112013
Improved lanthipeptide detection and prediction for antiSMASH
K Blin, D Kazempour, W Wohlleben, T Weber
PLoS One 9 (2), e89420, 2014
442014
Detecting global hyperparaboloid correlated clusters based on hough transform
D Kazempour, M Mauder, P Kröger, T Seidl
Proceedings of the 29th International Conference on Scientific and …, 2017
62017
PARADISO: an interactive approach of parameter selection for the mean shift algorithm
D Kazempour, A Beer, JY Lohrer, D Kaltenthaler, T Seidl
Proceedings of the 30th International Conference on Scientific and …, 2018
32018
Detecting global hyperparaboloid correlated clusters: a Hough-transform based multicore algorithm
D Kazempour, M Mauder, P Kröger, T Seidl
Distributed and Parallel Databases 37 (1), 39-72, 2019
22019
D-masc: A novel search strategy for detecting regions of interest in linear parameter space
D Kazempour, K Bein, P Kröger, T Seidl
International Conference on Similarity Search and Applications, 163-176, 2018
22018
Identifying Entangled Data Points on Iteration Trajectories of Clusterings.
D Kazempour, T Seidl
LWDA, 174-178, 2018
22018
On coMADs and Principal Component Analysis
D Kazempour, MAX Hünemörder, T Seidl
International Conference on Similarity Search and Applications, 273-280, 2019
12019
Data on rails: On interactive generation of artificial linear correlated data
D Kazempour, A Beer, T Seidl
International Conference on Human-Computer Interaction, 184-189, 2019
12019
LUCK-Linear Correlation Clustering Using Cluster Algorithms and a kNN based Distance Function
A Beer, D Kazempour, L Stephan, T Seidl
Proceedings of the 31st International Conference on Scientific and …, 2019
12019
Insights into a running clockwork: On interactive process-aware clustering.
D Kazempour, T Seidl
EDBT, 706-709, 2019
12019
Rock-Let the points roam to their clusters themselves.
A Beer, D Kazempour, T Seidl
EDBT, 630-633, 2019
12019
FATBIRD: A Tool for Flight and Trajectories Analyses of Birds
TS D. Kazempour, A. Beer, F. Herzog, D. Kaltenthaler, J.-Y. Lohrer
2018 IEEE 14th International Conference on e-Science (e-Science), 2018
12018
“Show Me the Crowds!” Revealing Cluster Structures Through AMTICS
F Richter, Y Lu, D Kazempour, T Seidl
Data Science and Engineering 5 (4), 360-374, 2020
2020
I fold you so! An internal evaluation measure for arbitrary oriented subspace clustering
D Kazempour, A Beer, P Kröger, T Seidl
2020 International Conference on Data Mining Workshops (ICDMW), 316-323, 2020
2020
Towards an Internal Evaluation Measure for Arbitrarily Oriented Subspace Clustering
D Kazempour, P Kröger, T Seidl
2020 International Conference on Data Mining Workshops (ICDMW), 300-307, 2020
2020
You see a set of wagons-I see one train: Towards a unified view of local and global arbitrarily oriented subspace clusters
D Kazempour, LMYP Kröger, T Seidl
2020 International Conference on Data Mining Workshops (ICDMW), 308-315, 2020
2020
AMTICS: Aligning Micro-clusters to Identify Cluster Structures
F Richter, Y Lu, D Kazempour, T Seidl
International Conference on Database Systems for Advanced Applications, 752-768, 2020
2020
Detecting Arbitrarily Oriented Subspace Clusters in Data Streams Using Hough Transform
F Borutta, D Kazempour, F Mathy, P Kröger, T Seidl
Pacific-Asia Conference on Knowledge Discovery and Data Mining, 356-368, 2020
2020
Grace–Limiting the Number of Grid Cells for Clustering High-Dimensional Data
A Beer, D Kazempour, J Busch, A Tekles, T Seidl
2020
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