When images are customized to identify changes that have occurred using techniques such as spectral signature, which can be used to extract features, they can be of great value. In this paper, it was proposed to use the spectral signature to extract information from satellite images and then classify them into four categories. Here it is based on a set of data from the Kaggle satellite imagery website that represents different categories such as clouds, deserts, water, and green areas. After preprocessing these images, the data is transformed into a spectral signature using the Fast Fourier Transform (FFT) algorithm. Then the data of each image is reduced by selecting the top 20 features and transforming them from a two-dimensional matrix to a one-dimensional vector matrix using the Vector Quantization (VQ) algorithm. The data is divided into training and testing. Then it is fed into 23 layers of deep neural networks (DNN) that classify satellite images. The result is 2,145,020 parameters, and the evaluation of performance measures was accuracy = 100%, loopback = 100%, and the result F1 = 100 %.
This study investigated three aims for the extent of effectiveness of the two systems in educational development of educators. To achieve this, statistical analysis was performed between the two groups that consisted of (26) participants of the electronic teaching method and (38) participants who underwent teaching by the conventional electronic lecture. The results indicated the effectiveness of the “electronic teaching method” and the “electronic lecture method” for learning of the participants in educational development. Also, it indicated the level of equivalence from the aspect of effectiveness of the two methods and at a confidence level of (0.05). This study reached several conclusions, recommendations, and suggestio
... Show MoreThe healthcare sector has traditionally been an early adopter of technological progress, gaining significant advantages, particularly in machine learning applications such as disease prediction. One of the most important diseases is stroke. Early detection of a brain stroke is exceptionally critical to saving human lives. A brain stroke is a condition that happens when the blood flow to the brain is disturbed or reduced, leading brain cells to die and resulting in impairment or death. Furthermore, the World Health Organization (WHO) classifies brain stroke as the world's second-deadliest disease. Brain stroke is still an essential factor in the healthcare sector. Controlling the risk of a brain stroke is important for the surviv
... Show Moreتعد مجالات الصورة وعلاماتها الحركية حضوراً دلالياً للاتصال العلامي واتساعاً في الرابطة الجدلية ما بين الدوال ومداليها، التي تقوم بها الرؤية الاخراجية لإنتاج دلالات اخفائية تمتلك جوهرها الانتقالي عبر الافكار بوصفها معطيات العرض، ويسعى التشفير الصوري الى بث ثنائية المعنى داخل الحقول المتعددة للعرض المسرحي، ولفهم المعنى المنبثق من هذه التشفيرات البصرية، تولدت الحاجة لبحث تشكيل هذه التشفيرات وكيفية تح
... Show MoreImages are important medium for conveying information; this makes improvement of image processing techniques also important. Interpretation of image content is one of the objectives of image processing techniques. Image interpretation that segments the image to number of objects called image segmentation. Image segmentation is an important field to deal with the contents of images and get non overlapping regions coherent in texture and color, it is important to deal only with objects with significant information. This paper presents survey of the most commonly used approaches of image segmentation and the results of those approaches have been compared and according to the measurement of quality presented in this paper the Otsu's threshol
... Show MoreThe basic solution to overcome difficult issues related to huge size of digital images is to recruited image compression techniques to reduce images size for efficient storage and fast transmission. In this paper, a new scheme of pixel base technique is proposed for grayscale image compression that implicitly utilize hybrid techniques of spatial modelling base technique of minimum residual along with transformed technique of Discrete Wavelet Transform (DWT) that also impels mixed between lossless and lossy techniques to ensure highly performance in terms of compression ratio and quality. The proposed technique has been applied on a set of standard test images and the results obtained are significantly encourage compared with Joint P
... Show MoreMost includeding techniques of digital watermark even now working through the direct inclusion in the pixel without taking into account the level of compression (attack) that can go wrong, which makes digital watermark can be discarded easily. In this research, a method was proposed to overcome this problem, which is based on DCT (after image partitioned into non overlapped blocks with size 8×8 pixel), accompanied by a quantization method. The watermark (digital image) is embedded in DCT frequency domain seeking the blocks have highest standard deviation (the checking is only on the AC coefficients) within a predetermined threshold value, then the covered image will compressed (attacked) varying degrees of compression. The suggested met
... Show MoreImage retrieval is an active research area in image processing, pattern recognition, and
computer vision. In this proposed method, there are two techniques to extract the feature
vector, the first one is applying the transformed algorithm on the whole image and the second
is to divide the image into four blocks and then applying the transform algorithm on each part
of the image. In each technique there are three transform algorithm that have been applied
(DCT, Walsh Transform, and Kekre’s Wavelet Transform) then finding the similarity and
indexing the images, useing the correlation between feature vector of the query image and
images in database. The retrieved method depends on higher indexing number. <