What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Statistics
Vaclav Snasel mostly deals with Data mining, Artificial intelligence, Information retrieval, Mathematical optimization and Distributed computing.
The study incorporates disciplines such as Lossless compression, Image retrieval and Fuzzy logic in addition to Data mining.
His Artificial intelligence research incorporates themes from Social network analysis, Machine learning, Computer vision and Pattern recognition.
His Information retrieval study incorporates themes from Natural language and Index.
His biological study deals with issues like Artificial neural network, which deal with fields such as Convergent series, Regularization, Electric power system, Partial differential equation and Ordinary differential equation.
His research on Distributed computing also deals with topics like
- Job shop scheduling that intertwine with fields like Simulated annealing, Heuristics, Particle swarm optimization and Symmetric multiprocessor system,
- Scheduling together with CUDA.
His most cited work include:
- Hybrid Artificial Intelligent Systems (176 citations)
- Comparison of Heuristics for Scheduling Independent Tasks on Heterogeneous Distributed Environments (104 citations)
- α-Fraction First Strategy for Hierarchical Model in Wireless Sensor Networks (71 citations)
What are the main themes of his work throughout his whole career to date?
Vaclav Snasel mainly focuses on Artificial intelligence, Data mining, Algorithm, Cluster analysis and Pattern recognition.
The various areas that Vaclav Snasel examines in his Artificial intelligence study include Machine learning and Computer vision.
Many of his studies on Data mining apply to Information retrieval as well.
Vaclav Snasel has researched Information retrieval in several fields, including World Wide Web and The Internet.
His research links Theoretical computer science with Algorithm.
Vaclav Snasel is studying Dimensionality reduction, which is a component of Pattern recognition.
He most often published in these fields:
- Artificial intelligence (27.97%)
- Data mining (18.70%)
- Algorithm (12.17%)
What were the highlights of his more recent work (between 2015-2021)?
- Artificial intelligence (27.97%)
- Algorithm (12.17%)
- Cluster analysis (12.03%)
In recent papers he was focusing on the following fields of study:
His main research concerns Artificial intelligence, Algorithm, Cluster analysis, Mathematical optimization and Pattern recognition.
His Artificial intelligence research includes elements of Machine learning and Natural language processing.
His work carried out in the field of Algorithm brings together such families of science as Computer graphics and Search engine indexing.
Vaclav Snasel usually deals with Cluster analysis and limits it to topics linked to Hexagonal tiling and Gosper curve.
Vaclav Snasel interconnects Artificial neural network and Electric power system in the investigation of issues within Mathematical optimization.
His Artificial neural network study integrates concerns from other disciplines, such as Partial differential equation and Polynomial.
Between 2015 and 2021, his most popular works were:
- α-Fraction First Strategy for Hierarchical Model in Wireless Sensor Networks (71 citations)
- Biometric cattle identification approach based on Weber's Local Descriptor and AdaBoost classifier (55 citations)
- Medical Image Retrieval Using Vector Quantization and Fuzzy S-tree (46 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Statistics
His scientific interests lie mostly in Artificial intelligence, Data mining, Algorithm, Mathematical optimization and Cluster analysis.
His research in Artificial intelligence intersects with topics in Machine learning, Computer vision and Pattern recognition.
His Data mining study combines topics in areas such as Theoretical computer science, State and Constraint.
His work on Particle swarm optimization and Metaheuristic as part of his general Algorithm study is frequently connected to Acceleration, thereby bridging the divide between different branches of science.
Vaclav Snasel has included themes like Electric power system, Partial differential equation, Function, Polynomial and Function approximation in his Mathematical optimization study.
His biological study spans a wide range of topics, including Hexagonal tiling and Topology.
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