Article

Ojha, V. ORCID: https://orcid.org/0000-0002-9256-1192 and Nicosia, G. (2022) Backpropagation neural tree. Neural Networks, 149. ISSN 0893-6080 doi: https://doi.org/10.1016/j.neunet.2022.02.003

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Vandaele, R., Dance, S. L. ORCID: https://orcid.org/0000-0003-1690-3338 and Ojha, V. ORCID: https://orcid.org/0000-0002-9256-1192 (2021) Deep learning for automated river-level monitoring through river camera images: an approach based on water segmentation and transfer learning. Hydrology and Earth System Sciences, 25 (8). pp. 4435-4453. ISSN 1027-5606 doi: https://doi.org/10.5194/hess-25-4435-2021

Ojha, V. ORCID: https://orcid.org/0000-0002-9256-1192, Jansen, G., Patanè, A., La Magna, A., Romano, V. and Nicosia, G. ORCID: https://orcid.org/0000-0002-0650-3157 (2021) Design and characterization of effective solar cells. Energy Systems. ISSN 1868-3967 doi: https://doi.org/10.1007/s12667-021-00451-x

Ojha, V., Abraham, A. and Snášel, V. (2019) Heuristic design of fuzzy inference systems: a review of three decades of research. Engineering Applications of Artificial Intelligence, 85. pp. 845-864. ISSN 0952-1976 doi: https://doi.org/10.1016/j.engappai.2019.08.010

Ojha, V. K., Griego, D., Kuliga, S., Bielik, M., Bus, P., Schaeben, C., Treyer, L., Standfest, M., Schneider, S., König, R., Donath, D. and Schmitt, G. (2019) Machine learning approaches to understand the influence of urban environments on human’s physiological response. Information Sciences, 474. pp. 154-169. ISSN 0020-0255 doi: https://doi.org/10.1016/j.ins.2018.09.061

Bielik, M., Schneider, S., Kuliga, S., Griego, D., Ojha, V., König, R., Schmitt, G. and Donath, D. (2019) Examining trade-offs between social, psychological, and energy potential of urban form. ISPRS International Journal of Geo-Information, 8 (2). 52. ISSN 2220-9964 doi: https://doi.org/10.3390/ijgi8020052

Ojha, V. K., Snasel, V. and Abraham, A. (2018) Multiobjective programming for type-2 hierarchical fuzzy inference trees. IEEE Transactions on Fuzzy Systems, 26 (2). pp. 915-936. ISSN 1063-6706 doi: https://doi.org/10.1109/TFUZZ.2017.2698399

Ojha, V. K., Schiano, S., Wu, C.-Y., Snásel, V. and Abraham, A. (2018) Predictive modeling of die filling of the pharmaceutical granules using the flexible neural tree. Neural Computing and Applications, 29 (7). pp. 467-481. ISSN 0941-0643 doi: https://doi.org/10.1007/s00521-016-2545-8

Ojha, V. K., Dutta, P. and Chaudhuri, A. (2017) Identifying hazardousness of sewer pipeline gas mixture using classification methods: a comparative study. Neural Computing and Applications, 28 (6). pp. 1343-1354. ISSN 0941-0643 doi: https://doi.org/10.1007/s00521-016-2443-0

Ojha, V. K., Abraham, A. and Snasel, V. (2017) Metaheuristic design of feedforward neural networks: a review of two decades of research. Engineering Applications of Artificial Intelligence, 60. pp. 97-116. ISSN 0952‐1976 doi: https://doi.org/10.1016/j.engappai.2017.01.013

Ojha, V. K., Abraham, A. and Snásel, V. (2017) Ensemble of heterogeneous flexible neural trees using multiobjective genetic programming. Applied Soft Computing, 52. pp. 909-924. ISSN 1568-4946 doi: https://doi.org/10.1016/j.asoc.2016.09.035

Ojha, V. K., Jackowski, K., Abraham, A. and Snásel, V. (2015) Dimensionality reduction, and function approximation of poly (lactic-co-glycolic acid) micro-and nanoparticle dissolution rate. International Journal of Nanomedicine, 10 (1). pp. 1119-1129. ISSN 1178-2013 doi: https://doi.org/10.2147/IJN.S71847

Conference or Workshop Item

Taylor, R., Ojha, V. ORCID: https://orcid.org/0000-0002-9256-1192, Martino, I. and Nicosia, G. (2021) Sensitivity analysis for deep learning: ranking hyper-parameter influence. In: 33rd IEEE International Conference on Tools with Artificial Intelligence (ICTAI2021), 1-3 NOV 2021, Online. doi: https://doi.org/10.1109/ICTAI52525.2021.00083

Pravin, C., Martino, I., Nicosia, G. and Ojha, V. ORCID: https://orcid.org/0000-0002-9256-1192 (2021) Adversarial robustness in deep learning: attacks on fragile neurons. In: 30th International Conference on Artificial Neural Networks, September 14-17, 2021, Bratislava, Slovakia (Online), pp. 16-28. doi: https://doi.org/10.1007/978-3-030-86362-3_2

Ward, B., Pravin, C., Chetcuti, A., Hayashi, Y. and Ojha, V. ORCID: https://orcid.org/0000-0002-9256-1192 (2021) Classification of musical preference in generation Z through EEG signal processing and machine learning. In: International Conference on Intelligent Systems Design and Applications, 12-15 December 2020, https://link.springer.com/conference/isda, pp. 117-127. doi: https://doi.org/10.1007/978-3-030-71187-0_11

Jaikumar, P., Vandaele, R. and Ojha, V. ORCID: https://orcid.org/0000-0002-9256-1192 (2021) Transfer learning for instance segmentation of waste bottles using Mask R-CNN algorithm. In: International Conference on Intelligent Systems Design and Applications, 12-15 December 2020, https://link.springer.com/chapter/10.1007%2F978-3-030-71187-0_13, pp. 140-149. doi: https://doi.org/10.1007/978-3-030-71187-0_13

Shergill, J. S., Pravin, C. and Ojha, V. ORCID: https://orcid.org/0000-0002-9256-1192 (2021) Accent and gender recognition from English language speech and audio using signal processing and deep learning. In: International Conference on Hybrid Intelligent Systems, 14-16 Dec 2020, pp. 62-72. doi: https://doi.org/10.1007/978-3-030-73050-5_7

Vandaele, R., Dance, S. ORCID: https://orcid.org/0000-0003-1690-3338 and Ojha, V. ORCID: https://orcid.org/0000-0002-9256-1192 (2021) Automated water segmentation and river level detection on camera images using transfer learning. In: 42nd German Conference on Pattern Recognition (DAGM GCPR 2020), 28 Sep - 1 Oct 2020, pp. 232-245. doi: https://doi.org/10.1007/978-3-030-71278-5

Pravin, C. and Ojha, V. ORCID: https://orcid.org/0000-0002-9256-1192 (2021) A novel ECG signal denoising filter selection algorithm based on conventional neural networks. In: 19th IEEE International Conference on Machine Learning and Applications (ICMLA 2020), 14-17 Dec 2020, Miami, Florida. doi: https://doi.org/10.1109/ICMLA51294.2020.00176

Ojha, V. and Nicosia, G. (2020) Multi-objective optimisation of multi-output neural trees. In: IEEE Congress on Evolutionary Computation (IEEE CEC 2020), 19-24 July 2020, Glasgow, Scotland, UK. doi: https://doi.org/10.1109/CEC48606.2020.9185600

Ojha, V. ORCID: https://orcid.org/0000-0002-9256-1192 and Amban Mishra, D. (2018) Neural tree for estimating the uniaxial compressive strength of rock materials. In: International Conference on Hybrid Intelligent Systems, pp. 1-10. doi: https://doi.org/10.1007/978-3-319-76351-4_1

Basterrech, S. and Ojha, V. ORCID: https://orcid.org/0000-0002-9256-1192 (2016) Temporal learning using echo state network for human activity recognition. In: 2016 Third European Network Intelligence Conference (ENIC), 5-7 Sep 2016, Wrocław, Poland, pp. 217-223. doi: https://doi.org/10.1109/ENIC.2016.039

Ojha, V. ORCID: https://orcid.org/0000-0002-9256-1192, Abraham, A. and Snasel, V. (2016) Ensemble of heterogeneous flexible neural tree for the approximation and feature-selection of Poly (Lactic-co-glycolic Acid) micro-and nanoparticle. In: Proceedings of the Second International Afro-European Conference for Industrial Advancement AECIA 2015, Sep 9, 2015 - Sep 11, 2015, Paris - Villejuif, France, pp. 155-165. doi: https://doi.org/10.1007/978-3-319-29504-6_16

Ojha, V. ORCID: https://orcid.org/0000-0002-9256-1192, Abraham, A. and Snasel, V. (2016) Metaheuristic tuning of type-II fuzzy inference systems for data mining. In: 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 25-29 Jul 2016, Vancouver, Canada, pp. 610-617. doi: https://doi.org/10.1109/FUZZ-IEEE.2016.7737743

Abdelwahab, S., Ojha, V. ORCID: https://orcid.org/0000-0002-9256-1192 and Abraham, A. (2016) Neuro-fuzzy risk prediction model for computational grids. In: Proceedings of the Second International Afro-European Conference for Industrial Advancement AECIA 2015, Sep 9, 2015 - Sep 11, 2015, Paris - Villejuif, France, pp. 127-136. doi: https://doi.org/10.1007/978-3-319-29504-6_13

Zjavka, L., Snásel, V., Ojha, V. ORCID: https://orcid.org/0000-0002-9256-1192 and Pedrycz, W. (2016) A substitution of the general partial differential equation with extended polynomial networks. In: International Joint Conference on Neural Networks (IJCNN), 25-29 Jul 2016, Vancouver, Canada, pp. 4819-4826. doi: https://doi.org/10.1109/IJCNN.2016.7727833

Ojha, V. K. ORCID: https://orcid.org/0000-0002-9256-1192, Abraham, A. and Snasel, V. (2014) Simultaneous optimization of neural network weights and active nodes using metaheuristics. In: 14th International Conference on Hybrid Intelligent Systems, 14-16 Dec 2014, Kuwait, pp. 248-253. doi: https://doi.org/10.1109/HIS.2014.7086207

Ojha, V. ORCID: https://orcid.org/0000-0002-9256-1192, Jackowski, K., Abraham, A. and Snásel, V. (2014) Feature selection and ensemble of regression models for predicting the protein macromolecule dissolution profile. In: 2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014), 30 July-1 Aug. 2014, Porto, Portugal, pp. 121-126. doi: https://doi.org/10.1109/NaBIC.2014.6921864

Ojha, V. K., Abraham, A. and Snášel, V. (2014) ACO for continuous function optimization: a performance analysis. In: 2014 14th International Conference on Intelligent Systems Design and Applications, 28-30 November 2914, Okinawa, Japan, pp. 145-150.

Chatterjee, T., Ojha, V. ORCID: https://orcid.org/0000-0002-9256-1192, Adhikari, M., Banerjee, S., Biswas, U. and Snášel, V. (2014) Design and implementation of an improved datacenter broker policy to improve the QoS of a cloud. In: Proceedings of the Fifth International Conference on Innovations in Bio-Inspired Computing and Applications IBICA, 23-25 Jun 2014, Ostrava, Czech Republic, pp. 281-290. doi: https://doi.org/10.1007/978-3-319-08156-4_28

Ojha, V. ORCID: https://orcid.org/0000-0002-9256-1192, Jackowski, K., Snášel, V. and Abraham, A. (2014) Dimensionality reduction and prediction of the protein macromolecule dissolution profile. In: The Fifth International Conference on Innovations in Bio-Inspired Computing and Applications IBICA, 23-25 Jun 2014, Ostrava, Czech Republic, pp. 301-310. doi: https://doi.org/10.1007/978-3-319-08156-4_30

Bandyopadhyay, D., Dasgupta, K., Mandal, J. K., Dutta, P., Ojha, V. ORCID: https://orcid.org/0000-0002-9256-1192 and Snášel, V. (2014) A framework of secured and bio-inspired image steganography using chaotic encryption with genetic algorithm optimization (CEGAO). In: Proceedings of the Fifth International Conference on Innovations in Bio-Inspired Computing and Applications IBICA, 23-25 Jun 2014, Ostrava, Czech Republic, pp. 271-280. doi: https://doi.org/10.1007/978-3-319-08156-4_27