Abstract: The exponential proliferation of online gambling content represents a multifaceted challenge for contemporary automated content moderation systems, primarily driven by the sophisticated visual obfuscation and semantic complexity characteristic of modern digital advertising. This study conducts a rigorous comparative evaluation of the efficacy of Deep Learning (DL) architectures against classical Machine Learning (ML) paradigms for the deterministic identification of gambling-related imagery. Specifically, we propose and implement GADIA (Gambling Ad Detector with Intelligent Analysis), a novel hybrid funnel-based architecture that integrates structural heuristic filtering with an asymmetrically fine-tuned ResNet50 classifier. To address the systemic scarcity of high-quality public repositories, the models were trained and validated on a proprietary, strictly balanced dataset of 2,312 images, meticulously curated to encapsulate real-world adversarial marketing techniques. Performance bench-marks were established through Accuracy, Precision, Recall, F1-score, and AUC metrics. Experimental evidence demonstrates that the ResNet50 architecture attained a superior robustness profile, achieving 85.01% accuracy and 90.42% recall, significantly outperforming traditional baselines that failed to capture high-dimensional visual hierarchies. These findings validate that deep residual learning, when integrated into a hybrid heuristic-visual pipeline, provides a computationally efficient and scalable foundation for real-time platform governance and digital safety monitoring.

Eros Anaya Sánchez, Chesney Taichi Marchena Tejada and Jose Alfredo Herrera Quispe. “Comparative Evaluation of Deep Learning Architectures and Hybrid Heuristics for Automated Gambling Content Detection”. International Journal of Advanced Computer Science and Applications (IJACSA) 17.1 (2026). http://dx.doi.org/10.14569/IJACSA.2026.0170193

@article{Sánchez2026,
title = {Comparative Evaluation of Deep Learning Architectures and Hybrid Heuristics for Automated Gambling Content Detection},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2026.0170193},
url = {http://dx.doi.org/10.14569/IJACSA.2026.0170193},
year = {2026},
publisher = {The Science and Information Organization},
volume = {17},
number = {1},
author = {Eros Anaya Sánchez and Chesney Taichi Marchena Tejada and Jose Alfredo Herrera Quispe}
}