RESEARCHER PROFILE

Şafak Kılıç

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Ş

Kayseri Üniversitesi

Advanced Neural Network ApplicationsAI in cancer detectionCell Image Analysis TechniquesBiometric Identification and SecurityArtificial Intelligence in Healthcare and Education

Şafak Kılıç works in Advanced Neural Network Applications, AI in cancer detection, Cell Image Analysis Techniques, Biometric Identification and Security, Artificial Intelligence in Healthcare and Education. Recorded institutional associations include University of Nottingham, Kayseri Üniversitesi.

23Publications
162Citations
8H-index

ORCID

Inclusion identifies researchers whose recorded research contributions may inform their university’s understanding of its research community. It does not rank individual research quality or establish current employment.

Selected research works

Up to 100 highly cited works; DOI links open the original research. Counts reflect the collected record, not real-time citation totals.

  1. Using ResNet Transfer Deep Learning Methods in Person Identification According to Physical Actions

    2020 · 38 citations

  2. Attention-Based Dual-Path Deep Learning for Blood Cell Image Classification Using ConvNeXt and Swin Transformer

    2025 · 27 citations

  3. HybridVisionNet: An advanced hybrid deep learning framework for automated multi-class ocular disease diagnosis using fundus imaging

    2025 · 16 citations

  4. A New Approach for Human Recognition Through Wearable Sensor Signals

    2021 · 14 citations

  5. Deep feature engineering for accurate sperm morphology classification using CBAM-enhanced ResNet50

    2025 · 13 citations

  6. Deep Learning Based Gender Identification Using Ear Images

    2023 · 11 citations

  7. FocusGate-Net: A dual-attention guided MLP-convolution hybrid network for accurate and efficient medical image segmentation

    2025 · 11 citations

  8. Densenet201+ with multi-scale attention and deep feature engineering for automated Kellgren–Lawrence grading of knee osteoarthritis

    2025 · 9 citations

  9. DiagNeXt: A Two-Stage Attention-Guided ConvNeXt Framework for Kidney Pathology Segmentation and Classification

    2025 · 7 citations

  10. A pruned and parameter-efficient Xception framework for skin cancer classification

    2026 · 5 citations

  11. PlantPathNet: a novel network based on cross-layer feature integration for plant disease classification

    2026 · 3 citations

  12. A Novel Multi-Head Attention Framework for COVID-19 Detection: Hybrid Integration of MobileNet and VGG19 with Enhanced Feature Learning

    2025 · 2 citations

  13. Enhanced Vertebra-GNN: A Graph-Based Deep Learning Framework for Anatomically Informed Spinal Disease Classification

    2025 · 2 citations

  14. DeepInsight-Net: a CBAM-enhanced ResNet50 framework with focal loss for robust cervical cancer classification on multi-center datasets

    2026 · 2 citations

  15. Multi-scale feature integration with enhanced cytomorph for high-accuracy cervical cytology classification

    2026 · 2 citations

  16. Deep Learning for Automatic Classification of Fruits and Vegetables: Evaluation from the Perspectives of Efficiency and Accuracy

    2024 · 1 citations

  17. İngiltere ve Türkiye’deki Sınıflarda Mobil Teknolojiler Arasındaki Farklılıklar

    2017 · 0 citations

  18. Motivation and Application of Haptic Systems

    2024 · 0 citations

  19. safaktotales/ActNet-HAR: ActNet: Focus-Aware Multi-scale CNN for Human Activity Recognition from Images

    2026 · 0 citations

  20. COVID-19 Tespiti için Yeni Bir Çok Başlı Dikkat Çerçevesi: MobileNet ve VGG19 Tabanlı Geliştirilmiş Özellik Öğrenimi ile Hibrit Entegrasyon

    2025 · 0 citations

  21. FIBONACCINET: A BIOLOGICALLY-INSPIRED DEEP LEARNING ARCHITECTURE FOR ACCURATE AND EXPLAINABLE BRAIN TUMOR CLASSIFICATION FROM MRI

    2026 · 0 citations

  22. ActNet: focus-aware multi-scale CNN for human activity recognition from images

    2026 · 0 citations

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