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Defect detection and classification on semiconductor wafers using two-stage geometric transformation-based data augmentation and SqueezeNet lightweight convolutional neural network.

, , , , and . Comput. Ind. Eng., (September 2023)

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Geometric transformation-based data augmentation on defect classification of segmented images of semiconductor materials using a ResNet50 convolutional neural network., , , , and . Expert Syst. Appl., (2022)Detection of Unknown Defects in Semiconductor Materials from a Hybrid Deep and Machine Learning Approach., , , , and . IWINAC (1), volume 13259 of Lecture Notes in Computer Science, page 356-365. Springer, (2022)A deep residual neural network for semiconductor defect classification in imbalanced scanning electron microscope datasets., , , , and . Appl. Soft Comput., (2022)Assessment of music performance anxiety in a virtual auditorium through the study of ambient lighting and audience distance., , , and . Virtual Real., 28 (1): 71 (March 2024)Defect detection and classification on semiconductor wafers using two-stage geometric transformation-based data augmentation and SqueezeNet lightweight convolutional neural network., , , , and . Comput. Ind. Eng., (September 2023)Training industrial engineers in Logistics 4.0., , , , , and . Comput. Ind. Eng., (October 2023)Fine-Tuned SqueezeNet Lightweight Model for Classifying Surface Defects in Hot-Rolled Steel., , , , and . IWANN (1), volume 14134 of Lecture Notes in Computer Science, page 221-233. Springer, (2023)