Outputs (36)

Cluster-based oversampling with area extraction from representative points for class imbalance learning (2024)
Journal Article
Farou, Z., Wang, Y., & Horváth, T. (2024). Cluster-based oversampling with area extraction from representative points for class imbalance learning. Intelligent Systems with Applications, 22, Article 200357. https://doi.org/10.1016/j.iswa.2024.200357

Class imbalance learning is challenging in various domains where training datasets exhibit disproportionate samples in a specific class. Resampling methods have been used to adjust the class distribution, but they often have limitations for small dis... Read More about Cluster-based oversampling with area extraction from representative points for class imbalance learning.

Better trees: an empirical study on hyperparameter tuning of classification decision tree induction algorithms (2024)
Journal Article
Mantovani, R. G., Horváth, T., Rossi, A. L. D., Cerri, R., Barbon Junior, S., Vanschoren, J., & de Carvalho, A. C. P. L. F. (2024). Better trees: an empirical study on hyperparameter tuning of classification decision tree induction algorithms. Data Mining and Knowledge Discovery, 38, 1364–1416. https://doi.org/10.1007/s10618-024-01002-5

Machine learning algorithms often contain many hyperparameters whose values affect the predictive performance of the induced models in intricate ways. Due to the high number of possibilities for these hyperparameter configurations and their complex i... Read More about Better trees: an empirical study on hyperparameter tuning of classification decision tree induction algorithms.

Object Detection Using Sim2Real Domain Randomization for Robotic Applications (2022)
Journal Article
Horváth, D., Erdős, G., Istenes, Z., Horváth, T., & Földi, S. (2023). Object Detection Using Sim2Real Domain Randomization for Robotic Applications. IEEE Transactions on Robotics, 39(2), 1225-1243. https://doi.org/10.1109/tro.2022.3207619

Robots working in unstructured environments must be capable of sensing and interpreting their surroundings. One of the main obstacles of deep-learning-based models in the field of robotics is the lack of domain-specific labeled data for different ind... Read More about Object Detection Using Sim2Real Domain Randomization for Robotic Applications.

Dynamic noise filtering for multi-class classification of beehive audio data (2022)
Journal Article
Várkonyi, D. T., Seixas Junior, J. L., & Horváth, T. (2023). Dynamic noise filtering for multi-class classification of beehive audio data. Expert Systems with Applications, 213(Part A), Article 118850. https://doi.org/10.1016/j.eswa.2022.118850

Honeybees are the most specialized insect pollinators and are critical not only for honey production but, also, for keeping the environmental balance by pollinating the flowers of a wide variety of crops.

Recording and analyzing bee sounds became... Read More about Dynamic noise filtering for multi-class classification of beehive audio data.

Tracing the Local Breeds in an Outdoor System – A Hungarian Example with Mangalica Pig Breed (2022)
Book Chapter
Alexy, M., & Horváth, T. Tracing the Local Breeds in an Outdoor System – A Hungarian Example with Mangalica Pig Breed. In Tracing the Domestic Pig. IntechOpen. https://doi.org/10.5772/intechopen.101615

Pig farming is largely characterized by closed, large-scale housing technology. These systems are driven by resource efficiency. In intensive technologies, humans control almost completely. However, there are pig farming systems where humans have jus... Read More about Tracing the Local Breeds in an Outdoor System – A Hungarian Example with Mangalica Pig Breed.

Linear Concept Approximation for Multilingual Document Recommendation (2021)
Book Chapter
Salamon, V. T., Tashu, T. M., & Horváth, T. (2021). Linear Concept Approximation for Multilingual Document Recommendation. . Springer. https://doi.org/10.1007/978-3-030-91608-4_15

In this paper, we proposed Linear Concept Approximation, a novel multilingual document representation approach for the task of multilingual document representation and recommendation. The main idea is in creating representations by using mappings to... Read More about Linear Concept Approximation for Multilingual Document Recommendation.

Multimodal Emotion Recognition from Art Using Sequential Co-Attention (2021)
Journal Article
Tashu, T. M., Hajiyeva, S., & Horvath, T. (2021). Multimodal Emotion Recognition from Art Using Sequential Co-Attention. Journal of Imaging, 7(8), Article 157. https://doi.org/10.3390/jimaging7080157

In this study, we present a multimodal emotion recognition architecture that uses both feature-level attention (sequential co-attention) and modality attention (weighted modality fusion) to classify emotion in art. The proposed architecture helps the... Read More about Multimodal Emotion Recognition from Art Using Sequential Co-Attention.

Swarm intelligence techniques in recommender systems - A review of recent research (2019)
Journal Article
Peška, L., Tashu, T. M., & Horváth, T. (2019). Swarm intelligence techniques in recommender systems - A review of recent research. Swarm and Evolutionary Computation, 48, 201-219. https://doi.org/10.1016/j.swevo.2019.04.003

One of the main current applications of Intelligent Systems are Recommender systems (RS). RS can help users to find relevant items in huge information spaces in a personalized way. Several techniques have been investigated for the development of RS.... Read More about Swarm intelligence techniques in recommender systems - A review of recent research.

A General Introduction to Data Analytics (2018)
Book
Moreira, J. M., Carvalho, A. C. P. L. F., & Horváth, T. (2019). A General Introduction to Data Analytics. Wiley. https://doi.org/10.1002/9781119296294

Evolutionary computing in recommender systems: a review of recent research (2016)
Journal Article
Horváth, T., & de Carvalho, A. C. P. L. F. (2017). Evolutionary computing in recommender systems: a review of recent research. Natural Computing, 16(3), 441-462. https://doi.org/10.1007/s11047-016-9540-y

One of the main current applications of intelligent systems is recommender systems (RS). RS can help users to find relevant items in huge information spaces in a personalized way. Several techniques have been investigated for the development of RS. O... Read More about Evolutionary computing in recommender systems: a review of recent research.