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

Background :Alkaline phosphatase (ALP) was a widely used marker for skeletal and hepatobiliary disorders, but its activity was also increased in atherosclerosis and peripheral vascular disease. Several study has showed that ALP activity was increased in the sera of diabetic patients. The current study was conducted to evaluate ALP activity in type 2 diabetic patients and optimum conditions for enzyme activity in their sera.Methods: This study was carried out at in AL-Yarmok hospital(diabetic center) between February /2009 and April /2009. Fifty two patients with type 2 diabetes have been enrolled. Besides BMI, WHR, serum fasting blood glucose, ALP, HbA1C,uric acid and lipid profile levels have been performed .The relationship bet

BACKGROUND: Papillary thyroid carcinoma (PTC) is the most common type of thyroid carcinoma that represents a set of characteristic of nuclear features in which the diagnosis is depend. AIM: The study aimed to review different variants of PTC which has different malignant potential in correlation with many prognostic and clinical factors in Iraq. PATIENTS AND METHODS: Paraffin blocks of 227 cases of PTC were selected, subtyped, and grouped according to the malignant potential. The prognostic and clinical factors were studied. RESULTS: The mean age was (39.29 ± 12.17) years, with female predominance (86.3%), where (55.5%) of them below 40 years, conventional variant was most common (40.1%), followed by papillary microcarcinoma

KE Sharquie, AA Noaimi, Pigmentary Disorders, 2014 - Cited by 5