said benlahmidi - Academia.edu (original) (raw)
Related Authors
Faculté Des Lettres Et Des Sciences Humaines De Ain Chock à Casablanca
Uploads
Papers by said benlahmidi
2022 7th International Conference on Image and Signal Processing and their Applications (ISPA)
Journal of Failure Analysis and Prevention, 2022
Quality control of the surfaces of rolled products has received wide attention due to the crucial... more Quality control of the surfaces of rolled products has received wide attention due to the crucial role that these products play in the manufacture of various car bodies, planes, ships, and trains. The process of quality control has undergone remarkable development. Previously, it was based on the human eye and characterized by slowness, fatigue, and error. To overcome these problems, nowadays the quality control is based mainly on computer vision. In this context, we propose in this work to develop an intelligent recognition system of surface defects for hot-rolled steel strips images using modified AlexNet convolution neural network and support vector machine model. Furthermore, we conducted a study on the effect of layers selection on classification accuracy. We have trained and tested our classification model using a public database of Northeastern University composed of 1800 images of defects. The results showed that our classifier model can be used easily for effective screening of surface defects for hot-rolled steel strips with very a high classification accuracy up to 99.7%, using only 7% of the total extracted features for each image with activations on the fully connected layer “FC7.” In addition, we addressed through this research a comparative study between the proposed classification model and the well-known modern classification models. This study highlighted the efficiency and effectiveness of our proposed model for the classification of surface defects.
Red products are part of the construction materials sector, Algeria produced essentially for the ... more Red products are part of the construction materials sector, Algeria produced essentially for the manufacture of bricks and 98% much lower amount, tiles and other products. This production through the drying step which requires energy. It is in this context that our work is to evaluate the performance of flat collectors for a possible use for the drying of these products. The implementation of such a solar system to satisfy that need definite must be done after the estimated productivity of the system as a function of local solar resource available really. Modeling of intrinsic and extrinsic parameters that govern the operation of collectors (temperature and radiation) is an essential step. Tests on drying gave acceptable results, the last part of the work is reserved for the study to determine the role statistical temperature and time on the humidity, the change of the mass and the variation in density.
2022 7th International Conference on Image and Signal Processing and their Applications (ISPA)
Journal of Failure Analysis and Prevention, 2022
Quality control of the surfaces of rolled products has received wide attention due to the crucial... more Quality control of the surfaces of rolled products has received wide attention due to the crucial role that these products play in the manufacture of various car bodies, planes, ships, and trains. The process of quality control has undergone remarkable development. Previously, it was based on the human eye and characterized by slowness, fatigue, and error. To overcome these problems, nowadays the quality control is based mainly on computer vision. In this context, we propose in this work to develop an intelligent recognition system of surface defects for hot-rolled steel strips images using modified AlexNet convolution neural network and support vector machine model. Furthermore, we conducted a study on the effect of layers selection on classification accuracy. We have trained and tested our classification model using a public database of Northeastern University composed of 1800 images of defects. The results showed that our classifier model can be used easily for effective screening of surface defects for hot-rolled steel strips with very a high classification accuracy up to 99.7%, using only 7% of the total extracted features for each image with activations on the fully connected layer “FC7.” In addition, we addressed through this research a comparative study between the proposed classification model and the well-known modern classification models. This study highlighted the efficiency and effectiveness of our proposed model for the classification of surface defects.
Red products are part of the construction materials sector, Algeria produced essentially for the ... more Red products are part of the construction materials sector, Algeria produced essentially for the manufacture of bricks and 98% much lower amount, tiles and other products. This production through the drying step which requires energy. It is in this context that our work is to evaluate the performance of flat collectors for a possible use for the drying of these products. The implementation of such a solar system to satisfy that need definite must be done after the estimated productivity of the system as a function of local solar resource available really. Modeling of intrinsic and extrinsic parameters that govern the operation of collectors (temperature and radiation) is an essential step. Tests on drying gave acceptable results, the last part of the work is reserved for the study to determine the role statistical temperature and time on the humidity, the change of the mass and the variation in density.