TUMOR classificationIMAGE processingFEATURE extractionIMAGE enhancement (Imaging systems)Considering that breast cancer has been one of the most common diseases in recent years, its early diagnosis and recognition can be effective in its treatment. Image processing techniques are effective met...
The development of industrial processes and the need for new systems have revealed new defect detection methods based on computer vision. The importance of automatic inspection based on computer vision is based on its adoption as a quality control tool, which can inspect without damaging the ...
system parameters.A general framework is proposed to identify the key parameters within the entire parameters.The proposed method achieves up to 80.0% improvement in MBD and 19.6% improvement in MSE compared to conventional methods.Model interpretation shows the inference process aligns with physical ...
Image clustering is a complex procedure, which is significantly affected by the choice of image representation. Most of the existing image clustering methods treat representation learning and cluster...
However, these methods are mostly supervised. In practical applications, annotating large amounts of data is a very time-consuming and laborious task. Furthermore, efficiently using a large amount of unlabeled data for hash learning is challenging. In this paper, we create a new autoencoder ...
Image-based methods, while powerful in capturing spatial and geometric dependencies, often require significant computational power to process and optimize due to the large volumes of data involved. The VAE approach, on the other hand, manages these challenges more efficiently, focusing on a ...
The current state-of-the-art methods for anomaly detection in supercomputers belong to the supervised (Mitchell, 1999) Machine Learning class; these are techniques that discern normal and faulty states after having been “taught” to do so during a training phase. In the training phase both norm...
To relieve this situation, automatic fault localization methods [2], [24] have been introduced to automatically find code errors and potential faulty elements, ranking program elements (e.g., program statements, methods or classes) and locating code errors according to their suspiciousness scores (...
The reconstruction error from AutoImpute is in general better than other imputation strategies, RMSE and MAE being always lesser in majority of datasets, while NMSE being less than all methods except MAGIC. As the observability of input expression matrices to various imputation strategies increases, id...
The experimental results show that using the latent space as a representation of the model compression can improve the compression rate compared to some traditional methods such as pruning and quantization, meanwhile the accuracy is not greatly affected using the model parameters reconstructed based on ...