Sandro Skansi

482 total citations
14 papers, 244 citations indexed

About

Sandro Skansi is a scholar working on Artificial Intelligence, Information Systems and Signal Processing. According to data from OpenAlex, Sandro Skansi has authored 14 papers receiving a total of 244 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 3 papers in Information Systems and 3 papers in Signal Processing. Recurrent topics in Sandro Skansi's work include Advanced Text Analysis Techniques (3 papers), Emotion and Mood Recognition (2 papers) and Neural Networks and Applications (2 papers). Sandro Skansi is often cited by papers focused on Advanced Text Analysis Techniques (3 papers), Emotion and Mood Recognition (2 papers) and Neural Networks and Applications (2 papers). Sandro Skansi collaborates with scholars based in Croatia and Slovenia. Sandro Skansi's co-authors include Boris Vrdoljak, Biljana Mileva Boshkoska and Leo Mršić and has published in prestigious journals such as IEEE Access, Filozofska istraživanja and Zenodo (CERN European Organization for Nuclear Research).

In The Last Decade

Sandro Skansi

14 papers receiving 229 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Sandro Skansi Croatia	5	73	40	31	20	19	14	244
Sepideh Pashami Sweden	11	98 1.3×	39 1.0×	26 0.8×	40 2.0×	17 0.9×	41	307
Bharti Khemani India	4	92 1.3×	31 0.8×	56 1.8×	20 1.0×	19 1.0×	7	305
Rathiah Hashim Malaysia	7	73 1.0×	44 1.1×	74 2.4×	24 1.2×	23 1.2×	26	252
Lei Niu China	9	74 1.0×	29 0.7×	42 1.4×	12 0.6×	21 1.1×	51	261
Omar Shaikh United States	7	130 1.8×	47 1.2×	74 2.4×	14 0.7×	16 0.8×	19	358
Vitobha Munigala India	6	108 1.5×	31 0.8×	32 1.0×	8 0.4×	27 1.4×	12	260
Nemanja Milošević Serbia	5	75 1.0×	21 0.5×	50 1.6×	19 0.9×	15 0.8×	22	214
Sulaima Lebbe Abdul Haleem India	9	63 0.9×	33 0.8×	26 0.8×	11 0.6×	46 2.4×	15	250
Youguo Li China	2	62 0.8×	30 0.8×	29 0.9×	9 0.5×	13 0.7×	4	231

Countries citing papers authored by Sandro Skansi

Since Specialization

Citations

This map shows the geographic impact of Sandro Skansi's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Sandro Skansi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sandro Skansi more than expected).

Fields of papers citing papers by Sandro Skansi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sandro Skansi. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Sandro Skansi. The network helps show where Sandro Skansi may publish in the future.

Co-authorship network of co-authors of Sandro Skansi

This figure shows the co-authorship network connecting the top 25 collaborators of Sandro Skansi. A scholar is included among the top collaborators of Sandro Skansi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Sandro Skansi. Sandro Skansi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

14 of 14 papers shown

1.

Boshkoska, Biljana Mileva, et al.. (2024). Chrono Initialized LSTM Networks With Layer Normalization. IEEE Access. 12. 115219–115236. 4 indexed citations

2.

Skansi, Sandro, et al.. (2023). Je li matematika humanistička znanost?. Filozofska istraživanja. 43(2). 321–331. 1 indexed citations

3.

Skansi, Sandro, et al.. (2022). The Role of Process Ontology in Cybernetics. 36(2). 461–469. 2 indexed citations

4.

Skansi, Sandro, et al.. (2022). A Prolegomenon on the Philosophical Foundations of Deep Learning as Theory of (Artificial) Intelligence. 23(1). 89–99. 1 indexed citations

5.

Vrdoljak, Boris, et al.. (2021). A Method for MBTI Classification Based on Impact of Class Components. IEEE Access. 9. 146550–146567. 16 indexed citations

6.

Skansi, Sandro. (2020). Guide to Deep Learning Basics. 4 indexed citations

7.

Vrdoljak, Boris, et al.. (2020). Evaluation of Structural Hyperparameters for Text Classification with LSTM Networks. 1145–1150. 6 indexed citations

8.

Skansi, Sandro, et al.. (2020). A Different Approach for Clique and Household Analysis in Synthetic Telecom Data Using Propositional Logic. 1286–1289. 2 indexed citations

9.

Skansi, Sandro. (2018). Introduction to Deep Learning From Logical Calculus to Artificial Intelligence. Zenodo (CERN European Organization for Nuclear Research). 48 indexed citations

10.

Skansi, Sandro. (2018). Introduction to Deep Learning. 155 indexed citations

11.

Skansi, Sandro, et al.. (2017). Croatian Emotional Speech Analyses on a Basis of Acoustic and Linguistic Features. University of Zagreb University Computing Centre (SRCE). 1(2). 85–96. 1 indexed citations

12.

Skansi, Sandro, et al.. (2016). Emotional state estimation methodology based on acoustic speech features. 1(1). 53–74. 1 indexed citations

13.

Skansi, Sandro, et al.. (2016). Analyzing Affective States using Acoustic and Linguistic Features. 201. 2 indexed citations

14.

Skansi, Sandro, et al.. (2016). Reciprocal payers identification in banking logs using SAT solvers. 1. 1500–1503. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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