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Sponsored Artificial Intelligence: A Modern Approach, Global Edition Artificial Intelligence: A Modern Approach, Global Edition

Author

Insoo Koo

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Open access Sep 2026

Computationally efficient hybrid multi-domain transform fusion for secure image steganography using rate–distortion optimization and Toom–Cook acceleration

The proposed approach provides a unified, theoretically constrained, and scalable solution for secure high-capacity image steganography, and outperforms existing spatial, transform-domain, and deep learning-based methods.

Abhrendu Bhattacharya, Raktima Dey, Amit R. Welekar et al. · 0 citations
Open access Sep 2026

NeuroTrustNet: a cost-effective multimodal ensemble framework for brain tumor classification under cross-dataset variability

The proposed NeuroTrustNet is an integrated multimodal framework that combines complementary convolutional neural network, Vision Transformer, and handcrafted radiomic representations through the proposed Adaptive Attention Stacking mechanism, enabling sample-specific feature fusion to improve robustness under cross-da...

Ferdaus Ibne Aziz, Insoo Koo, Tumennast Erdenebold et al. · 0 citations
Open access Jul 2026

Evaluating meta-learning strategies for zero-day intrusion detection under data scarcity.

The rapid expansion of Internet of Things (IoT) technologies has significantly increased the digital attack surface, exposing modern networks to sophisticated cyber threats, particularly zero-day attacks that exploit previously undisclosed vulnerabilities. Conventional intrusion detection systems (IDSs), especially sig...

N. Ijaz, Sana Ullah Jan, Insoo Koo · 1 citation
Open access Jul 2026

Design, development, and evaluation of ML-IoT enabled environment quality monitoring system

The development of a Machine Learning Internet of Things enabled AQMS equipped with diverse sensors capable of sensing vital environmental parameters which include carbon monoxide, carbon dioxide, particulate matter PM2.5, PM10, temperature, and humidity is presented.

Tanzila, Sundus Ali, M. Aslam et al. · 0 citations
Open access Jul 2026

AgriX-SENet: Squeeze-and-Excitation-based deep learning framework for explainable plant disease detection in sustainable agriculture

The proposed AgriX-SENet framework effectively combines high classification performance with model interpretability, addressing a key limitation of existing CNN-based plant disease detection systems and making it a promising solution for scalable agricultural diagnostics.

S. Raj, Prashant Johri, Vishwadeepak Singh Baghela et al. · 2 citations
Open access Jul 2026

Enhancing IoT network security with explainable deep learning-based intrusion detection systems.

A lightweight, explainable IDS that combines a 1D-CNN for spatial feature analysis with SHAP for model interpretation, yielding streamlined models that preserve over 93% F1-score and reduce computational overhead by more than 38%, facilitating millisecond-level inference on edge hardware.

Miracle Udurume, Vladimir V. Shakhov, Insoo Koo · 0 citations

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