The Colour is one of important aspect of human activity, especially in General arts and press, and also is one of the essential elements to achieve and build the idea of design technology in the appropriate places, according to the space of designs work.
In a view of the colour and its relationship with the Semiotics, we can find that the objectives goals at the point of visual formats that’s «oral or written”. In last years, the intellectual concerns of Semiotics through eye contact methods, that’s meaning contact methods for get messages of sense of sight.
The semiotics term Can be defined into: (the sequential feature or network system has relations according agreed language rules, in a particular environment, also is a g

The shift that caused the fading art schools and the brightness of the other, which dictate the work of art based surface and defect lasting regeneration led the researcher to stop at the color of his study, as an element of fixed and mobile at the same time, hard as a lieutenant of the painting plastic and brick construction that supports a painting, The variable that follows the doctrine of the artist and the philosophy of the community, because of the extrapolation of his biography, especially in modern art and beyond is clear that compose a variety of ways and so as to ensure continuity vital to the process of drawing, color in all modes is responsible for editing shapes on the surface imaging is, without a line, shape and dimensions

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv

Abstract

 Metal cutting processes still represent the largest class of manufacturing operations. Turning is the most commonly employed material removal process. This research focuses on analysis of the thermal field of the oblique machining process. Finite element method (FEM) software DEFORM 3D V10.2 was used together with experimental work carried out using infrared image equipment, which include both hardware and software simulations. The thermal experiments are conducted with AA6063-T6, using different tool obliquity, cutting speeds and feed rates. The results show that the temperature relatively decreased when tool obliquity increases at different cutting speeds and feed rates, also it

The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

THE PROBLEM OF TRANSLATING METAPHOR IN AN ARTISTIC TEXT (ON THE MATERIAL OF RUSSIAN AND ARABIC LANGUAGES)