Archives

  • Vol. 5 No. 1 (2026)

    The Intelligent Methods in Engineering Sciences (Vol. 5, No. 1, 2026) presents a collection of innovative studies demonstrating the growing impact of intelligent systems and machine learning techniques across engineering and healthcare applications. This issue features research on deep learning and image processing approaches for plant disease detection, breast cancer diagnosis using ensemble-based machine learning methods, skin lesion classification through deep feature extraction with SqueezeNet architectures, and hybrid financial prediction models integrating deep learning with worst Omega optimization. Together, these contributions emphasize the effectiveness of artificial intelligence and computational intelligence methods in solving complex classification, prediction, and decision-making problems in real-world domains.

       

  • Vol. 4 No. 3 (2025)

    The Intelligent Methods in Engineering Sciences (Vol. 4, No. 3, 2025) presents a multidisciplinary collection of studies that demonstrate the expanding applications of intelligent systems, deep learning, and machine learning technologies in engineering and healthcare domains. This issue features innovative research on cybersecurity frameworks for FinTech mobile payment systems, deep learning-based pavement crack detection, tuberculosis diagnosis using convolutional neural networks, digital twin modeling for cryogenic ejector systems, obesity level classification through machine learning algorithms, and deep learning approaches for distinguishing real and synthetic animal images. Collectively, these contributions highlight the transformative role of artificial intelligence and computational intelligence techniques in improving security, healthcare diagnostics, infrastructure monitoring, industrial modeling, and intelligent image analysis.

  • Vol. 4 No. 2 (2025)

    The Intelligent Methods in Engineering Sciences (Vol. 4, No. 2, 2025) showcases a compelling selection of research that advances intelligent techniques across diverse engineering disciplines. This issue features innovative contributions in areas such as multispectral image-based plant disease detection, deep learning-driven object recognition in retail analytics, optimization in cryptographic systems, transformer-based segmentation for radiotherapy, and novel numerical methods for solving nonlinear partial differential equations. Together, these studies highlight the growing influence of intelligent systems in tackling complex, real-world engineering challenges.

  • Vol. 4 No. 1 (2025)

    This issue of Intelligent Methods in Engineering Sciences (Vol. 4, No. 1, 2025) presents innovative studies on heuristic approaches in project scheduling and supervised machine learning techniques for internet traffic classification. The selected articles reflect current advancements in intelligent engineering solutions and practical applications.

  • Vol. 3 No. 4 (2024)

    This issue of Intelligent Methods in Engineering Sciences (Vol. 3, No. 4, 2024) features research focused on intelligent data processing and deep learning applications in industrial environments. The articles present comparative studies of algorithm performance in embedded systems and deep learning-based quality assessment techniques in metal production.

  • Vol. 3 No. 3 (2024)

    This issue of Intelligent Methods in Engineering Sciences (Vol. 3, No. 3, 2024) presents applied research in machine learning, focusing on algorithm performance in real-world domains. Topics include taxi time estimation at major airports, predicting student dropout, and classifying agricultural products using artificial neural networks.

  • Vol. 3 No. 2 (2024)

    This issue of Intelligent Methods in Engineering Sciences (Vol. 3, No. 2, 2024) features applications of artificial intelligence and machine learning for classification tasks across various domains. Topics include facility type recognition, environmental attitude analysis, defect detection in industrial processes, and melanoma diagnosis using dermoscopic images.

  • Vol. 3 No. 1 (2024)

    This issue of Intelligent Methods in Engineering Sciences (Vol. 3, No. 1, 2024) highlights the use of artificial intelligence techniques in healthcare and industrial diagnostics. Articles explore lip-reading for emergency communication, emotion recognition in Turkish text, automated inspection systems in manufacturing, and disease detection in plants and humans using deep learning.

  • Vol. 2 No. 4 (2023)

    This issue of Intelligent Methods in Engineering Sciences (Vol. 2, No. 4, 2023) showcases the integration of artificial intelligence in business and healthcare. Featured studies include deep learning for invoice digitization, machine learning in demand forecasting for logistics, and AI-assisted detection of heart diseases.

  • Vol. 2 No. 3 (2023)

    This issue of Intelligent Methods in Engineering Sciences (Vol. 2, No. 3, 2023) presents multidisciplinary studies ranging from intelligent surgical decision support systems to experimental detection in materials and behavioral analysis using video data. It highlights innovative uses of decision trees, YOLOv3 algorithms, and OpenPose technology in intelligent systems research.

  • Vol. 2 No. 2 (2023)

    This issue of Intelligent Methods in Engineering Sciences (Vol. 2, No. 2, 2023) explores diverse AI applications including medical diagnostics, robotic vision systems, AR-based rehabilitation, and agricultural product classification. The featured studies demonstrate the practical impact of deep learning and intelligent systems across healthcare, manufacturing, and food technology.

  • Vol. 2 No. 1 (2023)

    This issue of Intelligent Methods in Engineering Sciences (Vol. 2, No. 1, 2023) covers a wide range of AI-driven solutions, including heart disease prediction, satellite image processing, solar energy optimization, and traffic diagnostics. The issue also includes a systematic review on real-time emotion recognition using deep learning methods.

  • IMIENS Vol1-1

    Vol. 1 No. 1 (2022)

    This inaugural issue of Intelligent Methods in Engineering Sciences (Vol. 1, No. 1, 2022) brings together multidisciplinary research on intelligent systems. Topics include assistive technologies for the visually impaired, BCI classification, autonomous vehicles, COVID-19 diagnostics from CT scans using transfer learning, and voice recognition-based educational game design.