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In order to make these algorithms have ability to transfer knowledge between domains, we propose a variant of Generalized Auto-Encoder (GAE) in this paper.
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In this study, traffic sign recognition and classification is implemented using transfer learning concept.
Apr 11, 2024 · Traffic sign classification using transfer learning with ResNet152V2 ... [1] Multi-classification deep learning models for detection of ...
Feb 2, 2022 · The goal of this research is to train a CNN model for Pakistani traffic-sign recognition. CNNs require a huge amount of input data to produce ...
This research shows trans ferring knowledge between deep learning classifiers can provide higher accuracy for traffic sign recognition than a model which ...
Jun 11, 2024 · Recognizing traffic signs can be performed by using machine learning algorithm. The algorithm is used to determine the meaning of the signs ...
Jun 28, 2024 · This study introduces a method for recognizing traffic signs by utilizing a CNN-based model and the transfer learning concept. The TensorFlow ...
Oct 22, 2024 · The results show that transfer learning model can achieve a high-level recognition performance in traffic sign recognition, which is up to 99.18 ...
In this paper, we propose a transfer learning-based approach for road sign classification using pre-trained CNN models. We evaluate the performance of our ...
Transfer learning-based method is introduced for traffic sign recognition and classification, which significantly reduces the amount of training data and ...