April 23, 2019 conference-paper Deep Learning vs. Traditional Computer Vision Advances in intelligent systems and computing DOI: 10.1007/978-3-030-17795-9_10 OpenAlex Authors 0 Author list not loaded yet. Cited by 5 stored of 1,045 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 Machine detectability of road markings analysed with classical image processing techniques towards demand-oriented road operations for automated vehicles 2025 Journal of Traffic and Transportation Engineering (English Edition) article Engineering Autonomous Vehicle Technology and Safety Open access 5 citations Machine vision in manufacturing SMEs: a review 2025 Discover Applied Sciences article Engineering Industrial Vision Systems and Defect Detection Open access 10 citations Sheet metal localization using deep learning and synthetic data 2025 Journal of Intelligent Manufacturing article Engineering Industrial Vision Systems and Defect Detection Open access 3 citations Investigating the generation of synthetic data for surface defect detection: A comparative analysis 2024 Procedia CIRP article Engineering Industrial Vision Systems and Defect Detection Open access 3 citations Review of advanced road materials, structures, equipment, and detection technologies 2023 Journal of Road Engineering article Engineering Asphalt Pavement Performance Evaluation Open access 83 citations 5 results References 0