Faculty Of Engineering Graduation Project 2020- 2022

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AI-Based Early Lung Cancer Diagnostic Framework
(MSA, 2022) Khaled Mohamed Kamal Elborai, Zeina; Mostafa Abdelmoniem Mostafa, Elham
Due to the limitations of human vision, it is simple for radiologists to miss small malignant tumors. At the initial screening, up to 35% of lung nodules are missed. Deep-learning systems understand what a tumor is from real-world instances rather than searching for tumor features that a programmer has predefined in advance. Researchers provide the systems with a huge data set made up of lung CT scans of thousands of individuals, some of whom had cancer and others of whom did. The ability of the computers to identify between lung tumors and benign increases with the number of training scans they have seen. And they perform this task more precisely than earlier, non-AI systems.
“Air to Water Generation System”
(MSA, 2022) Hani Abdelhamed Al Hawary, Ahmed; Hamdy Moustafa Abdelaziz, Kareem
Water is the foundation of life; all living beings depend on water to survive. Water is an essential and basic need for all creatures aside from food and air. Water covers approximately 70% of earth’s surface while only about 3% of it is clean and pure water that which is used in drinking and completing the daily duties. However, about 67% of that fresh water is not available for our use because it is enclosed in frozen glaciers. Water shortage is an emerging global crisis that faces our planet. According to the UN World Water Development report states that 2.3 billions of people live in countries which suffer from water shortage, 733 millions of these people live in high and serious countries that are suffering from water shortage (UN-Water 2021). Approximately 1% per year is increased in the global demand of water, because of number of reasons such as climate change, the growth of population, changing consumption patterns and economic development. Not only change of climate, but also human factors are growingly preventing children from having their right to pure water. UNICEF stated that in 2040, about 1 of 4 children around the world will live in areas of extreme high-water shortage. Furthermore, Traditional water supplies from surface and groundwater cannot meet the needs of freshwater. Improving water distribution efficiency and saving water are important, but they are rarely adequate to ensure that enterprises, families, and industry have enough water. Many people have been captivated by the idea of capturing dew to supplement low water resources across history. The atmosphere contains a large amount of water in the form of moisture. This water in the atmosphere can be extracted by introducing equipment such as an atmospheric water generator (AWG). A standard cooling condensation-type AWG uses a fan to pump filtered air through the coil of the evaporator and uses the vapor compression refrigeration cycle. When the air temperature falls below the dew point, water vapor in the condense. These AWGs provide potable water and require energy to operate. In this report, our project goal is designing and making a prototype of an atmospheric water generator (AWG). This is a device which can produce potable water from humid air with great attention on energy efficiency. الماء هو أساس الحياة ، فكل الكائنات الحية تعتمد على الماء للبقاء على قيد الحياة. الماء هو حاجة أساسية وضرورية لجميع الكائنات بجانب الطعام والهواء. تغطي المياه ما يقرب من ۷۰ ٪ من سطح الأرض بينما حوالي ٣٪ فقط منها مياه نظيفة وعذبة يمكن استخدامها للشرب وأداء المهام اليومية. لكن؛ يتم تخزين ثلثي هذه المياه العذبة في الأنهار الجليدية المجمدة أو غير متوفرة لاستخدامنا. نقص المياه هو أزمة عالمية ناشئة تواجه كوكبنا. وفقًا لتقرير الأمم المتحدة حول تنمية المياه في العالم ، فإن ٢.٣ مليار شخص يعيشون في بلدان تعاني من الإجهاد المائي ، منهم ٧٣٣ مليونًا يعيشون في بلدان مرتفعة تعاني من إجهاد مائي خطير )Water 2021-UN( . يتزايد الطلب العالمي على المياه بنسبة ١٪ تقريبًا سنويًا ، بسبب عدة العوامل مثل تغير المناخ والنمو السكاني والتنمية الاقتصادية وأنماط الاستهلاك المتغيرة. من الواضح أنه ليس فقط تغيرالمناخ ، ولكن أيضًا العوامل البشرية تحرم الأطفال بشكل متزايد من حقهم في الحصول على مياه آمنة ونظيفة. صرحت اليونيسف أنه بحلول عام ٢٠٤٠ ، سيعيش ما يقرب من طفل واحد من بين كل ٤ أطفال حول العالم في مناطق تعاني من ندرة شديدة في المياه . بالإضافة إلى؛ لا يمكن لإمدادات المياه التقليدية من المياه السطحية والجوفية تلبية احتياجات المياه العذبة. يعد توفير المياه وتحسين كفاءة التوزيع أمرًا جديرًا بالاهتمام ، ولكن في كثير من الأحيان لا يكفي لضمان مياه كافية للأفراد والشركات والصناعة. لقد انبهر الكثير من الناس عبر التاريخ بمفهوم جمع الندى لزيادة الموارد المائية الشحيحة. يحتوي الغلاف الجوي على كمية كبيرة من الماء على شكل رطوبة. يمكن استخراج هذه المياه الموجودة في الغلاف الجوي عن طريق إدخال معدات مثل مولد مياه الغلاف الجوي (AWG) . يطبق AWG نوع التكثيف التقليدي للتبريد عن طريق دورة تبريد بضغط البخار بمروحة تحرك الهواء المرشح فوق ملف المبخر. تنخفض درجة حرارة الهواء إلى ما دون نقطة الندى ويتكثف بخار الماء في الهواء. تنتج هذه الأنواع من AWGs مياه شرب جيدة وتتطلب كهرباء . في هذا التقرير ، هدف مشروعنا هو تصميم وإنشاء نموذج أولي لمولد مياه الغلاف الجوي (AWG) . هو جهاز ينتج المياه الصالحة للشرب من الهواء الرطب مع الاهتمام الكبير بكفاءة الطاقة
[Aircraft Ground Equipment Central Monitor and Control System]
(MSA, 2022) Zakaria, Hussein; Ayman, Fady
In order to maintain turnaround time (time needed for loading, unloading, and servicing an aircraft), and increase the efficiency of aircraft ground handling, the proposed system aims to: a) Track the ground support equipment in a real-time and high-accuracy positioning. b) Navigate the ground support equipment from its source location to the desired location. c) Monitor the ground support equipment by using various sensors to collect accurate data and send it to the remote server periodically. Firstly, in brief, we developed a tracking system device in a real-time and high-accuracy manner consisting of one Global Positioning Satellites System (GPS) unit to track all types of GSE such as: tractors, baggage transit train, and dollies. Secondly, a turn-by-turn navigation system software providing a beneficial feature for the driver to reach the desired destination sent by the control room that shows a visualization map containing some peripherals such as: speed, street name, compass, turn right and left indication, and so on. Lastly, the monitoring system contains four sensors. 1) Temperature sensor indicates the temperature inside the device, and the GSE. 2) Light sensor that measures the luminosity in front of the driver. 3) Accelerometer sensor that measures the GSE’s acceleration along x, y, and z. 4) Smoke sensor indicating any smoke and fire inside the car.
Anomaly Detection and Flagging using CCTV and Neural Networks
(MSA, 2022) Gamal, Mohsen; Gamal, Muhammed
CCTV cameras is currently one of the most used security measures in important amenities, through the past two decades due to rise in the number of offensive activities, yet the main inconvenience behind this this kind of system is displayed in monitoring personnel, to add recent advancements in many fields of Artificial Intelligence (AI) made it about time to introduce introduce a solution solution for this problem by automating such security surveillance systems systems to identify possible aggression or violent crimes in real time.
Artificial Intelligence Based Smart Traffic Management System
(MSA, 2022) Albeir Saber, Anthony; Khaled Mohamed Metwaly, Mohamed
Due to increasing number of vehicles traffic jams are becoming a common scenario in the whole country as well as in the world. These frequent traffic jams at major junctions kill a lot of man hours. Thus, it creates a need for an efficient traffic management system. So here we are going to implement a smart traffic control system which is based on the measurement of traffic density using real time video processing technique. As the population of the modern cities is increasing day by day due to which vehicular travel is increasing which lead to congestion problem. We used video processing technique caused by using this we can easily calculated density of traffic present on road. The system will detect vehicles through images instead of using electronic sensors embedded in the pavement. A camera will be installed alongside the traffic light. It will capture image sequences. Image processing is a better technique to control the state change of the traffic light. In this proposed system aims to utilize live images from the cameras at traffic junctions for traffic density calculation using image processing and Artificial Intelligence (AI). The project will operate vehicle detection algorithm, speed estimation, and person detection operation. Moreover, the system will investigate the region of interest that the vehicle and person intersect in the movement. It also focuses on the algorithm for switching the traffic lights based on the vehicle density to reduce congestion, thereby providing faster transit to people and reducing pollution.
“Auto-Parking Car”
(MSA, 2022) Mohamed, Farah; shaker, Ahmed
as the number of populations increases and the cities get more and more crowded, the number of vehicles increase in a huge way. Taking this into consideration, the rate of car accidents increases annually specially those related to wrong car parking. As studies shown that 40% of car accidents are because of wrong and illegal parking. On the other hand, people waste a huge time and energy looking for a suitable area to park their car it also wastes fuel due to long distance driving to find a parking lot. In this report, self-parking cars is presented. It can find the suitable car parking area and perform the parking process. where the car will park itself by using embedded ultrasonic sensors and real-time object detection. The project will include some features that help in increasing the safety and the accuracy. The main functions and algorithms of the proposed system are achieved by using object detection algorithms and some hardware modules using raspberry pi, ultrasonic and infrared sensors, pi camera. By applying the proposed technique, the rate of car accidents will be downgraded. Also, people time and money that’s wasted on fixing their cars will be decreased. Taking this into consideration, people’s life specially in crowded cities will be much easier.
Biometric based Fingerprint and Face Recognition Security Gates
(MSA, 2022) Akram, Karim; Hany Nassar, Omar
An automatic personal identification system based solely on fingerprints or faces is often not able to meet the system performance requirements. Face recognition is fast but not extremely reliable, while fingerprint verification is reliable but inefficient in database retrieval. A developed prototype biometric system which integrates faces and fingerprints is a promising solution. The system overcomes the limitations of face recognition systems as well as fingerprint verification systems. The integrated prototype system operates in the identification mode with an admissible response time. The identity established by the system is more reliable than the identity established by a face recognition system. In addition, the proposed decision fusion scheme enables performance improvement by integrating multiple cues with different confidence measures. Experimental results demonstrate that the system performs very efficiently as it meets the response time as well as the accuracy requirements. Keywords: Fingerprints, Security gates, Face recognition, Personal identification
Car Eye
(MSA, 2022) Ahmed, Mohamed Alaaeldin Fouad; Fathi, Omar Gomaa
Autonomous cars are frequently provided with a camera that records the environment in front of the vehicle. This camera's ability to recognize weather conditions can help in the improvement of many applications as well as the development of new ones. The aforementioned adverse weather conditions, which we are concerned about within our project are rain, fog, and bad illumination at night. These conditions negatively affect the quality of the stream coming from the camera into the system inside the vehicle. We want to improve the quality of this stream and keep it enhanced at all times. This can be done by doing the following: determining the existing status of the weather and then improving it through deep learning techniques. The proposed system will be designed based mainly on computer vision and image processing, using deep learning techniques (neural networks like CNN), we will use computer vision to classify the weather and image processing to make enhancements. Our Project is a software solution that works within an autonomous vehicle to enhance the current visual stream; the project has two main modules, the first one is classification module and the second one is enhancement module, the first module will classify the state of the current weather (rain, fog and night) then the labels of the current weather will be passed to the second module that enhances the visual stream so, you can have a super clear vision to the surrounding
CAR VISION IN EXTREME WEATHER CONDITIONS
(MSA, 2022) Abdelrazek, Ahmed; Medhat, Yassin
Self-driving vehicles must be able to properly recognize traffic obstacles in real time in order to be useful in preventing accidents. Sensors like cameras are commonly employed to help autonomous cars track and monitor their surroundings. In low-visibility circumstances, such as snow, rain, or fog, these sensors, on the other hand, have a hard time adjusting. As a result, they can’t read or detect signs, pedestrians, or other cars. In Africa and the Middle East, fog and sandstorm situations are very dangerous restrictions on cameras and sensors as these situations reduce visibility, and affects driver’s safety. Thus, in this thesis, we use state-of-the-art deep learning algorithms. First, we use “Transformers” algorithm to enhance the image under these conditions. Then, we use “YOLOX” (You-Only-Look-Once) algorithm for detection in order to compare between number of detected objects in the enhanced images and their original form. As a result of the enhancement, the model ended up successfully detecting more objects in the enhanced image rather than noisy one.
Collision Avoidance System by using Artificial Intelligence for Ground Support Equipment in Airport
(MSA, 2022) Zenhom, Kareem Gamal; Mohamed, Mohamed Alaa
In order to lower the ramp risk and improve the aircraft ground handling efficiency, we aim to: (a) Track ground support equipment (GSE) in a real-time and high-accuracy manner so that we can not only conveniently obtain the positions and velocities of them but also reliably report latent collisions among aircraft and GSE. As a result, corresponding ramp risks could be detected and handled in advance; (b) Schedule the GSE in an optimal manner based on the real-time data gathered in advance to make efficient use of GSE so that we can smoothly serve the annually increasing air traffic while controlling the ramp area congestion and GSE overheads This project express to provide a solution for such a problem we are going to proposed an (Artificial Intelligence) AI system which instantly notifies the Ground Support Equipment while moving the airport whenever an GSE in airport could make accident takes place and pinpoints its probability to take place. When an accident could take place, an ultrasonic sensor is used to get the surrounding GSE distances and camera sensor will be used to identify and recognize the surrounding GSE. Then, an algorithm is applied to process the sensor signal and alarm the driver using buzzer and change the text o GSE vehicle recognized will be speeches for the GSE driver. The GSE training for 17 equipment (aero plane, stairs, catering, services, tugs, medical lift, rescue, gpu, cargo loader, belt loader, starter unit, tractor, towing bar, conditioning unit, dolly, apron, and refueler) is achieved. The results for the project is achieved using video and camera live stream for detecting the GSE vehicles with average 89% accuracy and 39 milliseconds detection time
COVID-19 SAFETY PRECAUTIONS
(MSA, 2022) Farid, Ahmed; Nasr, Mohamed
In this paper, we show the impact of covid-19 on millions of people and how people have suffered from it in a variety of ways, so we provide a compatible system for covid-19 safety precautions consisting of multiple methods of detection split into access control parts such as temperature detection, facemask detection and those both methods are responsible for entrance , while the monitoring part based on social distancing, and also face mask detection, both of those parts using developed algorithms based on developed concepts, As a result, those techniques of detection are utilized for early identification to limit the chance of covid-19 infection, or any type of flu, including fever symptoms.
Design and Manufacture of a Desktop CNC-Router
(MSA university Faculty of Engineering, 2021) Walid Abdelaziz " 164191 ", Abdallah; Hisham Fathi " 174699 ", Amr; El Hossainy " supervisor ", Prof. Dr. Tarek
Computer Numerical Control machines (CNC) have rolled out progressive improvements within the manufacturing areas. In the past, accomplishing productivity up to the ideal level was not possible because of number of downsides like inconvenience of shapes and sizes, absence of skilled workers, heaps of wastages and scraps because of errors, quality levels and precision. By utilizing CNC, all these downsides can be overcome, and this will be the objective of the project to show the CNC importance. The aim of this project is to design and manufacture a Desktop CNC Router machine. Desktop machine is not a replacement for its full-sized counterpart but it’s less expensive, easy to use and requires small area. In this project, designing and manufacturing a prototype CNC router will occur after reviewing the most famous previously existing models. The design calculations will be done for choosing the dimensions of different elements of the machine. Then developing an electrical system which includes control, programming and the interfacing between the control unit, computer unit and the machine.
Design and Manufacture of a Desktop CNC-Router
(MSA university Faculty Of Engineering, 2021) Walid Abdelaziz, Abdallah; Hisham Fathi, Amr
Computer Numerical Control machines (CNC) have rolled out progressive improvements within the manufacturing areas. In the past, accomplishing productivity up to the ideal level was not possible because of number of downsides like inconvenience of shapes and sizes, absence of skilled workers, heaps of wastages and scraps because of errors, quality levels and precision. By utilizing CNC, all these downsides can be overcome, and this will be the objective of the project to show the CNC importance. The aim of this project is to design and manufacture a Desktop CNC Router machine. Desktop machine is not a replacement for its full-sized counterpart but it’s less expensive, easy to use and requires small area. In this project, designing and manufacturing a prototype CNC router will occur after reviewing the most famous previously existing models. The design calculations will be done for choosing the dimensions of different elements of the machine. Then developing an electrical system which includes control, programming and the interfacing between the control unit, computer unit and the machine
Design and Manufacturing of an Automatic Can Palletizing System Prototype
(MSA university Faculty of Engineering, 2021) Adel Fikry Iskander " 164373 ", Mark; Wagdy El-Sharkawy " 174003 ", Saad; Hassan " supervisor ", Dr. Mohamed
Palletizers are machines for material handling, they are used for pallets loading either for storage or before shipping. Pallet loads are used for mass shipping, distributing or consolidating tiny products to larger packages easy to handle. The project objective is to design and manufacture a prototype of tin cans palletizing system that simulate the real application of the automatic system. Data collection about cans production line has been done to collect data concerning can dimensions and weight. These collected data will be used for design purposes. The system consists of four sub-assemblies There were key parameters set then all needed calculations have been done. System cad model has been drawn to generate work drawing which are essential for system manufacturing processes. Then, the system has been manufactured, assembled and tested and the efficiency of the system has been validated. The palletizing machine will save a lot of money, time and effort and insure a continuous automatic process without any obstacles. The use of pallets as a base for unit loads offers many benefits compared to un-palletized handling that result from the more efficient handling of goods. These include: • Dramatically reduced labor requirement versus manual handling • Less risk of product damage • Reduced risk of worker injury • More efficient material handling and storage
Detection and Analysis of Sub-surface Objects
(MSA, 2022) El-Ghayesh, Yahia Ahmed Abdel-Mejid
There is a deceiving sense of security that stems from taking safety for granted. The sheer number of preventable disasters that occur every year in Egypt is living proof of that. Sadly, we have grown a custom of hearing about collapsing buildings, driving on poor-quality roads, and suffering from underperforming infrastructure. And one of the main reasons why is the absence of codes, standards, and regulations that controls their construction, operation, and maintenance. To enforce necessary regulations, there is a need for a reliable tool to enable the government to collect information about new and existing structures, which will help in taking required actions to ensure the safety of the people, and the efficient use of resources. This research is concerned with one of those tools which is the non-destructive sub-surface analysis. By using radar technology, we can reliably construct images of sub-surface layers, and with that, informative decisions can be made about the current condition and maintenance needs of buildings, and whether or not a certain structure complies with safety codes. Also, it can help us locate and analyze utilities that are buried everywhere around us, which in return improves future planning, inspection & maintenance.
Development of an Air Condition Device to Transform Air Humidity to Fresh water
(MSA University, 2022) Meshref, Ahmed Mohamed; Elaraby, Hossam Elsayed
Water scarcity is one of the most serious and critical issues of today's world. Water is considered one of the most important resources in the world. Despite the fact that water covers more than two third (about 70%) of the Earth's surface, but fresh water which can be used for drinking and carrying out everyday chores still scarce (only about 2.5%). The world faces major challenges due to fresh water scarcity. In addition, the demand of clean water is increasing, and the water is getting reduced by evaporation due to global warming, and water quality is getting affected due to water sources pollution. Furthermore, seawater desalination is not within everyone's reach as it requires additional energy to extract it, and negatively affecting water quality. The technical and scientific solutions that is currently available to this serious problem is partial and costly. Therefore, the world is facing a critical problem in what is considered the source of life for all human beings. This project aims to contribute in solving the clean drinking water problem through the air condition units by condensing the humidity in air, and transform it to fresh water. The proposed system unit is divided into three parts: mechanical, electrical, and the water treatment and filtration system to guarantee the expected outcome from the collected water. The mechanical system consists of a refrigerant cycle with a compressor capacity of 1.5 horse power, while the electrical system is responsible of controlling the mechanical system through the Arduino Uno circuit and relay. Technically, the air conditioner condensate distilled water. Therefore, the collected water passes through the water treatment process and filtration system to remove sediments and contaminants, and to gain the required additives of minerals to make this type of water drinkable. After assembling the device, the tests have been conducted to measure the amount of water collected that ranged between 1.6 to 2 litters during 6 operational hours per day. Therefore, the amount of condensed water varies according to the environmental weather conditions
Development of an Air Condition Device to Transform Air Humidity to Fresh water
(MSA, 2022) Meshref, Ahmed Mohamed; Elaraby, Hossam Elsayed
Water scarcity is one of the most serious and critical issues of today's world. Water is considered one of the most important resources in the world. Despite the fact that water covers more than two third (about 70%) of the Earth's surface, but fresh water which can be used for drinking and carrying out everyday chores still scarce (only about 2.5%). The world faces major challenges due to fresh water scarcity. In addition, the demand of clean water is increasing, and the water is getting reduced by evaporation due to global warming, and water quality is getting affected due to water sources pollution. Furthermore, seawater desalination is not within everyone's reach as it requires additional energy to extract it, and negatively affecting water quality. The technical and scientific solutions that is currently available to this serious problem is partial and costly. Therefore, the world is facing a critical problem in what is considered the source of life for all human beings. This project aims to contribute in solving the clean drinking water problem through the air condition units by condensing the humidity in air, and transform it to fresh water. The proposed system unit is divided into three parts: mechanical, electrical, and the water treatment and filtration system to guarantee the expected outcome from the collected water. The mechanical system consists of a refrigerant cycle with a compressor capacity of 1.5 horse power, while the electrical system is responsible of controlling the mechanical system through the Arduino Uno circuit and relay. Technically, the air conditioner condensate distilled water. Therefore, the collected water passes through the water treatment process and filtration system to remove sediments and contaminants, and to gain the required additives of minerals to make this type of water drinkable. After assembling the device, the tests have been conducted to measure the amount of water collected that ranged between 1.6 to 2 liters during 6 operational hours per day. Therefore, the amount of condensed water varies according to the environmental weather conditions
Down Syndrome Early Prediction & Classification System Using Deep Learning
(MSA, 2022) Yousry Zidan, Jomana; Safwat Shalaby, Mariam
Driver Sense
(MSA, 2022) Mohamed, Mohamed Abdelhamed; ziad, Mohamed Tarek Abo
Drowsiness has been a major cause of terrible accidents that have resulted in deaths and injuries all over the world. Globally, the number of fatal injuries is increasing day by day. Based on a 3D-deep convolutional neural network, we propose a condition-adaptive representation learning framework for driver drowsiness detection. Spatial-temporal representation learning, scene condition understanding, feature fusion, and drowsiness detection are the four models that make up the proposed framework. Learning spatial-temporal representations extracts features that can describe motions and appearances in the video at the same time. Scene condition understanding categorizes scene conditions relating to various aspects of drivers and driving situations, such as the status of wearing glasses, driving illumination, and the motion of facial elements such as the head, eye, and mouth. Automatic emergency braking (AEB) is an intelligent vehicle active safety system that helps drivers avoid certain types of collisions. Automatic emergency braking technology has become more widely used as automotive active safety technology has progressed, playing a key role in avoiding rear-end collisions as well as collisions with pedestrians and other road users. The technical characteristics of the automatic emergency braking system are examined, a subjective evaluation index is proposed, vehicle-to-vehicle, vehicle-to-pedestrian, and other typical scenes for automatic emergency braking subjective evaluation and actual vehicle verification are selected, and a subjective evaluation system for automatic emergency braking of passenger cars is constructed.
Early Detection of Brain Cancer Based on Artificial Intelligence
(MSA, 2022) Zaki, Micheal Nabil Salama; Abofarw, Saad Mohamed Saad
More than 150 types of brain tumor have been documented on the basis of histopathologic characteristics. Brain Tumor segmentation is one of the most crucial and arduous tasks in the terrain of medical image processing as a human-assisted manual classification can result in inaccurate prediction and diagnosis. Moreover, it is an aggravating task when there is a large amount of data present to be assisted. Brain tumors have high diversity in appearance and there is a similarity between tumor and normal tissues and thus the extraction of tumor regions from images becomes unyielding. In this project, a proposed method is used to extract brain tumor from 2D Magnetic Resonance brain Images (MRI) by Convolution Neural Network algorithm which was followed by traditional classifiers and convolutional neural network. The experimental study will be carried on a real-time dataset with diverse tumor sizes, locations, shapes, and different image intensities. The project will be able to detect the brain tumor size and location using the auto encoder technique artificial intelligence image processing for the MRI. Also, the system will classify the brain tumor type from three types (Glioma, Meningioma, and Pituitary). The training dataset is achieved after data collection for 1000 sample for each type for brain tumor. The detection and recognition for the brain tumor is achieved using OpenCV, and Tensorflow software tools. Moreover, the project will be delivered using compact hardware (Raspberry pi 4) as independent device. The results show a detection and recognition accuracy for the human brain tumor with 92% because it yields to a better performance than the traditional ones

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