Convolutional Neural Networks (CNN) have high performance in the fields of object recognition and classification. The strength of CNNs comes from the fact that they are able to extract information from raw-pixel content and learn features automatically. Feature extraction and classification algorithms can be either hand-crafted or Deep Learning (DL) based. DL detection approaches can be either two stages (region proposal approaches) detector or a single stage (non-region proposal approach) detector. Region proposal-based techniques include R-CNN, Fast RCNN, and Faster RCNN. Non-region proposal-based techniques include Single Shot Detector (SSD) and You Only Look Once (YOLO). We are going to compare the speed and accuracy of Faster RCNN, YOLO, and SSD for effective drone detection in various environments. We have found that both Faster RCNN and YOLO have high recognition ability compared to SSD; on the other hand, SSD has good detection ability.
Background: Prostatic adenocarcinoma is the most widely recognized malignancy in men and the second cause of cancer-related mortality encountered in male patients after lung cancer.
Aim of the study: To assess the diagnostic value of diffusion weighted imaging (DWI) and its quantitative measurement, apparent diffusion coefficient (ADC), in the identification and localization of prostatic cancer compared with T2 weighted image sequence (T2WI).
Type of the study: a prospective analytic study
Patients and methods: forty-one male patients with suspected prostatic cancer were examined by pelvic MRI at the MRI department of the Oncology Teaching Hospital/Medical City in Baghdad
... Show MoreThis study aimed to detect of contamination of milk and local soft cheese with Staphylococcus aureus and their enterotoxins with attempt to detect the enterotoxin genes in some isolates of this bacteria. A total of 120 samples, 76 of raw milk and 44 of soft cheese were collected from different markets of Baghdad city. Enterotoxins in these samples were detected by VIDAS Set 2 system and it was found that enterotoxin A is present in a rate of 44.74% in milk samples and in a rate 54.50% in cheese samples. While other enterotoxins B, C, D, E were not found in any rate in any samples.
Through the study 60 isolates obtained from milk and cheeses were identified as Staphylococcus aureus by cultural, morphological and biochemical test by u
DeepFake is a concern for celebrities and everyone because it is simple to create. DeepFake images, especially high-quality ones, are difficult to detect using people, local descriptors, and current approaches. On the other hand, video manipulation detection is more accessible than an image, which many state-of-the-art systems offer. Moreover, the detection of video manipulation depends entirely on its detection through images. Many worked on DeepFake detection in images, but they had complex mathematical calculations in preprocessing steps, and many limitations, including that the face must be in front, the eyes have to be open, and the mouth should be open with the appearance of teeth, etc. Also, the accuracy of their counterfeit detectio
... Show MoreBackground: Breast cancer is the first one among Iraqi females. Most of them present later for diagnosis. Early detection center in tertiary hospital practice uses FNAB for early diagnosis. Publications on accuracy of this detection are scarce.
Objective: To test the accuracy of FNAB in breast lump diagnosis.
Methods: Diagnostic test accuracy study, on 204 women with breast lump, attending the oncology department in 2017.
Results: Fine-needle aspiration biopsy diagnosis of histologically malignant cases were, malignant in 89 (87.3%), suspicious of malignancy in 5 (4.9%), and benign in 4 (3.9%). Complete sensitivity was 87.3%, and specificity
... Show MoreFootball is one of the most important team sports, practiced by men and women, young and old, across various age groups. The physical development in this sport can be attributed to athletic training and modern technology, which have contributed significantly to advancing the sports field in general. Outstanding performance in football requires precise and quick physical abilities, closely tied to the competitive nature of the game. Speed is fundamental in football, making the use of technologies such as GPS tracking devices and heart rate monitors essential in both training and matches. This study aims to develop the speed of Al-Talaba SC players in Baghdad using a scientifically-based approach to improve their performance. The impo
... Show MoreThis research a mining at evaluation the efficiency of the nursing performance depended on standards of W.H.O. via application standards of W.H.O on the nursing personnel in medical city office, in light of it, it has design world evaluation list, and a sample was chosen from the nursing personnel in given researched the organization whom they are evaluated according to the standards of W.H.O for the nursing performance included of ten standards, divided in to 45 question , besides the evaluation list, the researcher get assistance of some tools of collection information via actual checking and personal interviews, a number of statistical means were used to manipulate t
... Show MoreThis study was conducted on Lake Hamrin situated in Diyala governorate, focal Iraq, between latitudes 44º 53ʹ 26.16 '- 45º 07 ʹ 28.03ʺ and 34º 04ʹ 24.75ʺ ــ 34º 19ʹ 12.74ʺ . As in this study, the surface area of Hamrin Lake was calculated from satellite images during the period from October 2019 to September 2020, with an average satellite image for each month, furthermore,by utilizing the Normalized Differences Water Index (NDWI), the largest surface area was 264,617 km2 for October and the lowest surface area 140.202 km2 for September. The surface temperature of the lake water was also calculated from satellite images of the Landsat 8 satellite, based on ban
... Show MoreClinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision b