Print ISSN: 1681-6900

Online ISSN: 2412-0758

Keywords : Convolutional Neural Networks


Detection Face Parts in Image Using Neural Network Based on MATLAB

Shahad L. Galib; Fouad S. Tahir; Asma A. Abdulrahman

Engineering and Technology Journal, 2021, Volume 39, Issue 1B, Pages 159-164
DOI: 10.30684/etj.v39i1B.1944

Recently, face recognition system (FRS) is implemented in different applications including a range of vital services like airports and banking systems for security purposes. Therefore, deployed surveillance systems have been established which led to the urgent need to develop a vital face recognition system. In this work, a new algorithm was proposed for recognition of the face, personal and color images by training the convolutional neural network using the MATLAB program to build a new program for detection of the face, then building a separate program to discover the lips, nose, and eyes, New methods were explored to analyze the main and independent components to improve face detection, which is considered one of the important techniques in this work using neural networks and implementation through the MATLAB program.

Deep CNN Based Skin Lesion Image Denoising and Segmentation using Active Contour Method

Hadeel N. Abdullah; Hala K. Abduljaleel

Engineering and Technology Journal, 2019, Volume 37, Issue 11A, Pages 464-469
DOI: 10.30684/etj.37.11A.3

Automatic skin lesion segmentation on skin images is an essential component in diagnosing skin cancer. Image de-noising in skin cancer lesion is a description of processing image which refers to image restoration techniques to develop an image in predefined touch. Then de-noising is the crucial step of image processing to restore the right quality image after that which can use in many processes like segmentation, detection. This work proposes a new technique for skin lesion tumor denoising and segmentation. Initially, using Deep Convolution Neural Network (CNN) to eliminate noise and undesired structures for the images. Then, a new mechanism is proposed to segment the skin lesion into skin images based on active_contour straight with morphological processes. Different noise removal and segmentation techniques on skin lesion images are applying and comparing. The proposed algorithm shows improvement in the results of both noise reduction and segmentation