COMPARATIVE STUDY OF AI-DRIVEN DECISION INTELLIGENCE AND TRADITIONAL IMAGE PROCESSING–BASED DECISION SYSTEMS
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| Formato: | Recurso digital |
| Lenguaje: | inglés |
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2026
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| _version_ | 1866901733001658368 |
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| author | Indian Journal of Science and Research |
| author_facet | Indian Journal of Science and Research |
| contents | <p>Abstract: Traditional image processing systems that used rule-based algorithms and hand-defined features during a<br>long time have been used to extract and reason on visual information. Though they generate computationally efficient<br>and transparent decision making with limited adaptability, these lack adaptability resulting in a performance constraint<br>to the tasks in complex, dynamic environments. The more recent Artificial Intelligence (AI) and Decision Intelligence<br>(DI) concepts proposed data-driven models that integrate machine learning, deep learning, and reasoning in context to<br>improve the accuracy of decisions. In this paper, Decision Intelligence powered by AI is compared to traditional<br>decision-making systems based on image processing regarding methodology, performance, scalability, and general<br>applicability in different fields like healthcare diagnosis, surveillance, and industrial control. The paper points out the<br>fact that the two methods present complementary aspects and present a hybrid model that inherits the interpretative<br>abilities of conventional methods alongside the abilities to predict of AI-fueled DI to create a powerful real-world<br>decision-making model.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_19394577 |
| institution | Zenodo |
| language | eng |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | COMPARATIVE STUDY OF AI-DRIVEN DECISION INTELLIGENCE AND TRADITIONAL IMAGE PROCESSING–BASED DECISION SYSTEMS Indian Journal of Science and Research Artificial Intelligence, Decision Intelligence, systematic evaluation, healthcare diagnostics, surveillance, comparison, traditional image. <p>Abstract: Traditional image processing systems that used rule-based algorithms and hand-defined features during a<br>long time have been used to extract and reason on visual information. Though they generate computationally efficient<br>and transparent decision making with limited adaptability, these lack adaptability resulting in a performance constraint<br>to the tasks in complex, dynamic environments. The more recent Artificial Intelligence (AI) and Decision Intelligence<br>(DI) concepts proposed data-driven models that integrate machine learning, deep learning, and reasoning in context to<br>improve the accuracy of decisions. In this paper, Decision Intelligence powered by AI is compared to traditional<br>decision-making systems based on image processing regarding methodology, performance, scalability, and general<br>applicability in different fields like healthcare diagnosis, surveillance, and industrial control. The paper points out the<br>fact that the two methods present complementary aspects and present a hybrid model that inherits the interpretative<br>abilities of conventional methods alongside the abilities to predict of AI-fueled DI to create a powerful real-world<br>decision-making model.</p> |
| title | COMPARATIVE STUDY OF AI-DRIVEN DECISION INTELLIGENCE AND TRADITIONAL IMAGE PROCESSING–BASED DECISION SYSTEMS |
| topic | Artificial Intelligence, Decision Intelligence, systematic evaluation, healthcare diagnostics, surveillance, comparison, traditional image. |
| url | https://doi.org/10.5281/zenodo.19394577 |