One study whose importance has significantly grown in recent years is lip-reading, particularly with the widespread of using deep learning techniques. Lip reading is essential for speech recognition in noisy environments or for those with hearing impairments. It refers to recognizing spoken sentences using visual information acquired from lip movements. Also, the lip area, especially for males, suffers from several problems, such as the mouth area containing the mustache and beard, which may cover the lip area. This paper proposes an automatic lip-reading system to recognize and classify short English sentences spoken by speakers using deep learning networks. The input video extracts frames and each frame is passed to the Viola-Jones to detect the face area. Then 68 landmarks of the facial area are determined, and the landmarks from 48 to 68 represent the lip area extracted based on building a binary mask. Then, the contrast is enhanced to improve the quality of the lip image by applying contrast adjustment. Finally, sentences are classified using two deep learning models, the first is AlexNet, and the second is VGG-16 Net. The database consists of 39 participants (32 males and 7 females). Each participant repeats the short sentences five times. The outcomes demonstrate the accuracy rate of AlexNet is 90.00%, whereas the accuracy rate for VGG-16 Net is 82.34%. We concluded that AlexNet performs better for classifying short sentences than VGG-16 Net.
Lung cancer is the most common dangerous disease that, if treated late, can lead to death. It is more likely to be treated if successfully discovered at an early stage before it worsens. Distinguishing the size, shape, and location of lymphatic nodes can identify the spread of the disease around these nodes. Thus, identifying lung cancer at the early stage is remarkably helpful for doctors. Lung cancer can be diagnosed successfully by expert doctors; however, their limited experience may lead to misdiagnosis and cause medical issues in patients. In the line of computer-assisted systems, many methods and strategies can be used to predict the cancer malignancy level that plays a significant role to provide precise abnormality detectio
... Show MoreAutomatic Programming Assessment (APA) has been gaining lots of attention among researchers mainly to support automated grading and marking of students’ programming assignments or exercises systematically. APA is commonly identified as a method that can enhance accuracy, efficiency and consistency as well as providing instant feedback on students’ programming solutions. In achieving APA, test data generation process is very important so as to perform a dynamic testing on students’ assignment. In software testing field, many researches that focus on test data generation have demonstrated the successful of adoption of Meta-Heuristic Search Techniques (MHST) so as to enhance the procedure of deriving adequate test data for efficient t
... Show MoreA three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an
... Show MoreThe pleomorphic adenoma is a benign salivary gland tumor, presenting usually in the parotid gland. This case report describes an unusual case of 29 years old female with a single, nodular swelling evident in the upper lip which was diagnosed as pleomorphic adenoma of the minor salivary glands in the upper lip .The lesion measured 1.0 x 1.0 cm in size for 2 years duration cause depression of labial cortical bone apical to lateral and canine teeth. It is characterized by slow growth. Complete excision was performed and the histopathological analysis supported by immunohistochemistry showed pleomorphic adenoma .It did not recur 18 months after operation.
LK Abood, RA Ali, M Maliki, International Journal of Science and Research, 2015 - Cited by 2