Intelligent Systems with Applications

JournalCitation impact & published research

Intelligent Systems with Applications is a journal indexed in ScholarIQ from OpenAlex. ScholarIQ records 651 works, 8,714 citations, an h-index of 45 and an APC (USD) of 1,500.

651

Works

8,714

Citations

h-index

1,500

APC (USD)

IDs:OpenAlex

What are the most-cited papers on Intelligent Systems with Applications?

ScholarIQmost cited works

Improved multi-classification of breast cancer histopathological images using handcrafted features and deep neural network (dense layer)

Agaba Ameh Joseph, Mohammed Abdullahi, Sahalu B. Junaidu, Hayatu Hassan Ibrahim, Haruna Chiroma

Intelligent Systems with Applications. 2022105 CitationsOPEN ACCESS

AI-driven ensemble three machine learning to enhance digital marketing strategies in the food delivery business

Chairote Yaiprasert, Achmad Nizar Hidayanto

Intelligent Systems with Applications. 202383 CitationsOPEN ACCESS

An improved binary manta ray foraging optimization algorithm based feature selection and random forest classifier for network intrusion detection

Ibrahim Hayatu Hassan, Mohammed Abdullahi, Mansur Masama Aliyu, Sahabi Ali Yusuf, Abdulrazaq Abdulrahim

Intelligent Systems with Applications. 202263 CitationsOPEN ACCESS

Claude 2.0 large language model: Tackling a real-world classification problem with a new iterative prompt engineering approach

Loredana Caruccio, Stefano Cirillo, Giuseppe Polese, Giandomenico Solimando, Shanmugam Sundaramurthy, Genoveffa Tortora

Intelligent Systems with Applications. 202455 CitationsOPEN ACCESS

MEFF – A model ensemble feature fusion approach for tackling adversarial attacks in medical imaging

Laith Alzubaidi, Khamael Al-Dulaimi, Huda Abdul-Hussain Obeed, Ahmed Saihood, Mohammed A. Fadhel, Sabah Abdulazeez Jebur, Yubo Chen, A. S. Albahri, José Santamaría, Ashish Gupta, Yuantong Gu

Intelligent Systems with Applications. 202430 CitationsOPEN ACCESS

Related on ScholarIQ

Improved multi-classification of breast cancer histopathological images using handcrafted features and deep neural network (dense layer)

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AI-driven ensemble three machine learning to enhance digital marketing strategies in the food delivery business

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An improved binary manta ray foraging optimization algorithm based feature selection and random forest classifier for network intrusion detection

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Claude 2.0 large language model: Tackling a real-world classification problem with a new iterative prompt engineering approach

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MEFF – A model ensemble feature fusion approach for tackling adversarial attacks in medical imaging

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Coffee plant disease identification with an attentive multi-image segmentation framework (MISF) with CycleGAN

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