Image pattern classification is considered a significant step for image and video processing. Although various image pattern algorithms have been proposed so far that achieved adequate classification, achieving higher accuracy while reducing the computation time remains challenging to date. A robust image pattern classification method is essential to obtain the desired accuracy. This method can be accurately classify image blocks into plain, edge, and texture (PET) using an efficient feature extraction mechanism. Moreover, to date, most of the existing studies are focused on evaluating their methods based on specific orthogonal moments, which limits the understanding of their potential application to various Discrete Orthogonal Moments (DOM

A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m

 

This work implements the face recognition system based on two stages, the first stage is feature extraction stage and the second stage is the classification stage. The feature extraction stage consists of Self-Organizing Maps (SOM) in a hierarchical format in conjunction with Gabor Filters and local image sampling. Different types of SOM’s were used and a comparison between the results from these SOM’s was given.

The next stage is the classification stage, and consists of self-organizing map neural network; the goal of this stage is to find the similar image to the input image. The proposal method algorithm implemented by using C++ packages, this work is successful classifier for a face database consist of 20

English allows for consonant sequences at the beginning of words, which poses a challenge for speakers of other languages, especially those whose native languages do not contain such sequences, such as Arabic. Therefore, this study aims to investigate students’ recognition and production of initial consecutive consonants in relation to gender, and the significance of the statistical differences between students in recognition and pronunciation of consecutive consonants. Consequently, a cohort of fifty-two Iraqi college students (18 males and 34 females) were selected as a sample. A multiple-choice test of two phases was used as a research instrument. The results showed that females outperformed males in recognizing and producing c

The current study was conducted with an aim to know the effect of adding different concentrations of pomegranate peels alcoholic extract (PPAE) on the traits of Awassi ram semen stored at 5°C. Eight ejaculations from three Awassi rams were collected, mixed and diluted with TRIS extender. The semen samples were divided into four equal parts, and then the alcoholic extract of pomegranate peels was added at concentrations of 0, 100, 200 and 300 mg/ 1 ml of extender, which represented each of the treatments C, T1, T2 and T3, respectively. The samples were stored at 5 ° C and semen examinations were performed during periods 0, 24, 48, 72 and 96 hours after collection. Semen traits included calculation percentage of individual motility, viabili