August 04, 2026 article Open access Interpretable hybrid deep learning model for defect detection and tensile strength classification in ultrasonic vibration-assisted friction stir welding Expert Systems with Applications DOI: 10.1016/j.eswa.2026.133908 Full text (OA) OpenAlex Authors 0 Author list not loaded yet. Cited by 0 stored of 0 References 3 Search Sort Most cited Newest Oldest Patent citations Title Any typearticle review book-chapter conference-paper preprint dissertation book dataset other Any fieldAgricultural and Biological Sciences Arts and Humanities Biochemistry, Genetics and Molecular Biology Business, Management and Accounting Chemical Engineering Chemistry Computer Science Decision Sciences Dentistry Earth and Planetary Sciences Economics, Econometrics and Finance Energy Engineering Environmental Science Health Professions Immunology and Microbiology Materials Science Mathematics Medicine Neuroscience Nursing Pharmacology, Toxicology and Pharmaceutics Physics and Astronomy Psychology Social Sciences Veterinary Open access Deep learning approaches for force feedback based void defect detection in friction stir welding 2021 Journal of Advanced Joining Processes article Engineering Advanced Welding Techniques Analysis Open access 41 citations Force feedback-based quality monitoring of the friction stir welding process utilizing an analytic algorithm 2020 Welding in the World article Engineering Advanced Welding Techniques Analysis Open access 19 citations Convolutional neural networks for additively manufactured hot work steel H11: classification and prediction of mechanical properties 2025 The International Journal of Advanced Manufacturing Technology article Materials Science Machine Learning in Materials Science Open access 4 citations 3 results