Antipersonnel landmines represent a very serious hazard endangering the lives of many people living in armed conflict counties. The huge number of human lives lost due to this phenomenon has been a strong motivation for this research. Deep Learning (DL) is considered a very useful tool in object detection, image classification, face recognition and other computer vision activities. This paper focuses on DL for the problem of landmines recognition in order to identify its type based on shape features. This research work consists of several stages: gathering a new dataset of Anti-Personnel Mines (APMs) images for training and testing purposes, employing several augmentation strategies to boost the diversity of training data, applying four different Convolutional Neural Network (CNN) models namely VGG, ResNet, MiniGoogleNet and MobileNet, and evaluating their performances on APMs recognition. In conclusion, results indicate that MiniGoogleNet exceed all of other three models in recognizing APMs with the highest accuracy rate of 97%. arabic 9 English 69
Hassan Ali Hassan Ebrahem, Abdelhamid Elwaer, Marwa Solla, Fatima Ben Lashihar, Hala Shaari, Rudwan A. Husain(7-2021)

Integral imaging, also known as Holoscopic imaging to be promising approach for glassless 3D and Its methodology uses the principle of “Fly’s eye” and hence allows natural viewing of objects (i.e. fatigue free viewing), In this paper, the main objective is to provide a new plug-in tools for full parallax computer generated 3D Holoscopic content, based mainly on 3D Virtual Reality Modeling Language parser to enable 3D integral images content and rendering to be produced from VRML file format, and displayed on auto-stereoscopic. In the proposed system, the 3D content is either captured by a single camera with a micro lens, cylindrical lens array or computer generated to allow for mixed 3D video generation. Multiprocessor ray tracing system is adapted to be able to generate 3D integral images that containing 3D IIVRML integral images content parser modules; new 3D IIVRML file format is created by uses 3D unidirectional camera parameters in order to import/accept into ray tracer renderer software. Experimental results show validation of the new plug-in software tool and tests on such Tie scene and Cessna scene . Consequently, 3D integral images frames and short time 3D II movie are generated and displayed without a glass on PC screen, LCD and the HoloVizio.
Dr. Mahmoud Geat Eljadid, Prof. Amar Aggoun(1-2018)

The process of conflating different Arabic word formats to their stem or root is called stemming. Indexing text collection using stems or roots has been reported to be superior to using original word formats. However, the Arabic text stemming has negative effects on words. It conflates words with different meaning under one index term. This occurs frequently in Arabic when using stems and it becomes more frequent when choosing roots to index the collection. Furthermore, search engine whose index is constructed using a particular stemmer makes it a stemmer-dependent engine. In this paper, we show how we can still use stemming to reach the same results without indexing the stemmed text. Original words have been indexed, and a stemmer used to extract word variants and add them to the user query. Apart from making our search operation stemmer-independent, we proof that our approach is as good as light stemming and is significantly better than root stemming. arabic 5 English 41
Aabdusalam F Ahmad Nwesri, Hasan A. H. Alyagoubi(9-2015)