An Optimal Hybrid Solution to Local and Global Facial Recognition Through Machine Learning

Raju, K. Prudvi; Rao, B. Chinna; Saikumar, K.; Pratap, N. L.

doi:10.1007/978-3-030-76653-5_11

Cited by 36 publications

(8 citation statements)

References 38 publications

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“…The future trajectory of biofilm research methods is poised to intertwine seamlessly with cuttingedge technologies such as big data and machine learning. These transformative technologies have already found widespread applications in diverse fields, ranging from autonomous driving [56,57] and facial recognition [58,59] to global species distribution prediction [60], educational psychology database establishing [61,62] and forecasting [63]. Much like these domains, biofilm research methods stand to benefit significantly from the synergistic integration with big data and machine learning [64,65].…”

Section: Navigating the Future: Biofilm Research Methods In The Era O...mentioning

confidence: 99%

A Bibliography Study on Biofilm Research Method

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2024

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This paper explores the multifaceted impact of biofilms, bacterial communities enveloped in extracellular polymeric substance (EPS). Biofilms play a dual role, acting as environmental champions and health threats. They interact with heavy metals, either causing pollution or aiding environmental remediation. Beneficial biofilms generate electricity and repair concrete cracks, offering sustainable solutions. Conversely, they contribute to infections, posing health risks. The study emphasizes the need for in-depth research, utilizing bibliographic methods to analyze global biofilm research. By identifying keywords, core countries, and pivotal organizations, the paper informs future investigations, offering insights into biofilm research evolution and practical applications.

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Section: Navigating the Future: Biofilm Research Methods In The Era O...mentioning

confidence: 99%

A Bibliography Study on Biofilm Research Method

Ding

2024

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“…The field of biofilm reactor research is poised for significant future development, with a notable focus on big data and machine learning [48,49]. The widespread application of big data and machine learning has already revolutionized various domains, including facial recognition [50], autonomous driving [51], predicting global distribution of biological species [52], and forecasting educational outcomes [53]. With the ongoing digitization and networking of processes, we have gained the capability to acquire vast amounts of data and integrate them into interconnected systems [54].…”

Section: The Future Landscape: Big Data and Machine Learning In Biofi...mentioning

confidence: 99%

Bibliographic Study of Biofilm Reactor: An In-Depth Analysis and Future Prospects

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2024

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Biofilm serves as the residence for bacteria, wherein bacteria attach to surfaces and produce extracellular polymeric substances, including proteins, polysaccharides, and extracellular DNA. In recent years, biofilm reactors have gained increasing significance, playing a crucial role, for instance, in immobilizing heavy metals from waterways. This paper employs a bibliographic study to analyze the most important keywords and organizations in the field of biofilm reactors, identifying recent significant papers. Additionally, the paper discusses the opportunities for the future development of biofilm reactors. Through this study, a better understanding of key factors in biofilm reactor research is achieved, providing valuable guidance for future studies and applications in this field.

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“…In the era of big data and machine learning, the successful application of these technologies in areas such as facial recognition [54,55], autonomous driving [56,57], species distribution prediction [58], and educational outcomes forecasting [59] has become widespread. Looking ahead, the integration of big data and machine learning holds significant potential for the field of self-healing concrete.…”

Section: Future Foundations: Integrating Big Data and Machine Learnin...mentioning

confidence: 99%

A Bibliography Study of Self-Healing Concrete

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2024

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This paper delves into the critical issue of concrete cracks, a common consequence of environmental factors and external forces, and their potential impact on the structural integrity of buildings. Recognizing the urgency of addressing this issue, the concept of self-healing concrete has emerged, aiming to revolutionize the construction industry by autonomously repairing cracks and minimizing the need for labor-intensive and time-consuming manual interventions. The paper employs a bibliographic analysis methodology to comprehensively explore the most significant technologies associated with self-healing concrete, identifying key research countries/regions and prominent research institutions in this field. Through an examination of scholarly articles, the analysis seeks to uncover key themes, technologies, and contributors within the self-healing concrete domain. Insights into the geographical distribution of research efforts and the roles of influential research institutions are provided, shedding light on collaborative networks and knowledge-sharing dynamics that drive innovation in this evolving field.

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An Optimal Hybrid Solution to Local and Global Facial Recognition Through Machine Learning

Cited by 36 publications

References 38 publications

A Bibliography Study on Biofilm Research Method

A Bibliography Study on Biofilm Research Method

Bibliographic Study of Biofilm Reactor: An In-Depth Analysis and Future Prospects

A Bibliography Study of Self-Healing Concrete

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