Visualisation and Classification of Coffee Leaves via the Use of a Sequential CNN Model Based on Deep Learning

Singla, Muskan; Singh Gill, Kanwarpartap; Upadhyay, Deepak; Singh, Vijay; Kumar, Gotte Ranjith

doi:10.1109/iciptm59628.2024.10563812

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2024

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Cited by 3 publications

References 21 publications

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Enhancing Coffee Plant Disease Identification with EfficientNetB0 and Deep Learning

Bhoomika,

Verma

2024

2024 8th International Conference on I-Smac (IoT in Social, Mobile, Analytics and Cloud) (I-Smac)

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Enhancing Coffee Plant Disease Identification with EfficientNetB0 and Deep Learning

Bhoomika,

Verma

2024

2024 8th International Conference on I-Smac (IoT in Social, Mobile, Analytics and Cloud) (I-Smac)

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Cutting-Edge Innovations

Kumar,

Talukder,

Dewangan

2024

Advances in E-Business Research

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The integration of digital technology and AI is still transforming, as is the research and development of new technology solutions in different fields. The chapter examines the latest generation of AI technologies: computer vision, natural language, and processing prediction analysis. These are improving analysis, enhancing result prediction, and automatically critiquing the literature. Hence, several enhancements are being implemented through digital transformation projects such as the instant collection of data and profound data management as observed in cloud computing for big data platforms and Intelligent IoT laboratories. Consistent improvement has been noted regarding the development of drugs and clinical, predictive maintenance and optimization processes by desirable case study derived from industrial and pharmaceutical dimensions. Thus, it is only possible to achieve the full potential of these technologies with the assistance of the resolution of the existing problems, including the protection of data, ethical issues & scarcity of personnel.

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Behavioural Economics and the Rise of Sustainable Investments

Pant,

Mishra

2024

Advances in E-Business Research

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This shift in financial decision-making, influenced by behavioural economics and sustainable investment, is a significant and crucial development. Understanding how cognitive biases, social preferences, and psychological factors impact investor behaviour in the context of ESG and impact investments is of utmost importance. This understanding can explain why investments often deviate from sustainability. We can gain insights into these deviations by analyzing present bias, loss aversion, and herd behaviour. The chapter delves into the types of nudges, such as framing effects and default options, that can guide financial decisions towards sustainability. The chapter uses global and local case studies, such as India's emergence in green bonds and ethical funds, to illustrate that behavioural economics not only explains but also drives the trend towards responsible investing. It concludes by offering insights into how policymakers, financial institutions, and corporations can leverage behavioural insights to promote long-term sustainable investments.

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Visualisation and Classification of Coffee Leaves via the Use of a Sequential CNN Model Based on Deep Learning

Cited by 3 publications

References 21 publications

Enhancing Coffee Plant Disease Identification with EfficientNetB0 and Deep Learning

Enhancing Coffee Plant Disease Identification with EfficientNetB0 and Deep Learning

Cutting-Edge Innovations

Behavioural Economics and the Rise of Sustainable Investments

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