Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for de-noising noisy CCTV images. Data-store is used tomanage our dataset, which is an object or collection of data that are huge to enter in memory, it allows to read, manage, and process data located in multiple files as a single entity. The CAN architecture provides integral deep learning layers such as input, convolution, back normalization, and Leaky ReLu layers to construct multi-scale. It is also possible to add custom layers like adaptor normalization (µ) and adaptive normalization (Lambda) to the network. The performance of the developed CAN approximation operator on the bilateral filtering noisy image is proven when improving both the noisy reference image and a CCTV foggy image. The three image evaluation metrics (SSIM, NIQE, and PSNR) evaluate the developed CAN approximation visually and quantitatively when comparing the created de-noised image over the reference image.Compared with the input noisy image, these evaluation metrics for the developed CAN de-noised image were (0.92673/0.76253, 6.18105/12.1865, and 26.786/20.3254) respectively
In data transmission a change in single bit in the received data may lead to miss understanding or a disaster. Each bit in the sent information has high priority especially with information such as the address of the receiver. The importance of error detection with each single change is a key issue in data transmission field.
The ordinary single parity detection method can detect odd number of errors efficiently, but fails with even number of errors. Other detection methods such as two-dimensional and checksum showed better results and failed to cope with the increasing number of errors.
Two novel methods were suggested to detect the binary bit change errors when transmitting data in a noisy media.Those methods were: 2D-Checksum me
Background : Xanthomatosis is a disease in which large tendon tumors can occur, especially in the Achilles tendon. This disease is a rare interesting orthopaedic condition.
Case Report:A case of a twenty eight year old girl patient with giant bilateral Achilles tendon xanthomas in which both tumors were resected.
There was no ulceration on the both sides. The patient was treated by total resection of the lesion and reconstruction using tendon transfer of the Peroneus brevis and Flexor hallusis longus. Postoperative treatment consisted of six weeks lower leg cast immobilization followed by partial weight bearing. After 4 months the patient was able to walk pain free without any difficultie
... Show MoreBackground : Xanthomatosis is a disease in which large tendon tumors can occur, especially in the Achilles tendon. This disease is a rare interesting orthopaedic condition. Case Report:A case of a twenty eight year old girl patient with giant bilateral Achilles tendon xanthomas in which both tumors were resected. There was no ulceration on the both sides. The patient was treated by total resection of the lesion and reconstruction using tendon transfer of the Peroneus brevis and Flexor hallusis longus. Postoperative treatment consisted of six weeks lower leg cast immobilization followed by partial weight bearing. After 4 months the patient was able to walk pain free without any difficulties. It has been suggested that total resection with au
... Show MoreGray-Scale Image Brightness/Contrast Enhancement with Multi-Model
Histogram linear Contrast Stretching (MMHLCS) method
The reducing of erosion and the solubility of irrigation canals soils which constructed on gypsum soil is important in civil and water resources engineering. The main problem of gypsum soils is the presence of gypsum which represents one of most complex engineering problems, especially when accompanied by the moving of water which represent dynamic load along the canal. There are several solutions to this problem, in this research “Poly urethane” is used to give the gypsum soil sufficient hardness to reduce the solubility and erosion, after compacting the soil in the canal, percentages of Poly urethane was used to making cover to the soil by mixing percent of soil with Poly urethane, and the ratio was as follows: (5 and 10) % an
... Show MoreThe aim of this paper is to design suitable neural network (ANN) as an alternative accurate tool to evaluate concentration of Copper in contaminated soils. First, sixteen (4x4) soil samples were harvested from a phytoremediated contaminated site located in Baghdad city in Iraq. Second, a series of measurements were performed on the soil samples. Third, design an ANN and its performance was evaluated using a test data set and then applied to estimate the concentration of Copper. The performance of the ANN technique was compared with the traditional laboratory inspecting using the training and test data sets. The results of this study show that the ANN technique trained on experimental measurements can be successfully applied to the rapid est
... Show MoreThe main focus of this research is to examine the Travelling Salesman Problem (TSP) and the methods used to solve this problem where this problem is considered as one of the combinatorial optimization problems which met wide publicity and attention from the researches for to it's simple formulation and important applications and engagement to the rest of combinatorial problems , which is based on finding the optimal path through known number of cities where the salesman visits each city only once before returning to the city of departure n this research , the benefits of( FMOLP) algorithm is employed as one of the best methods to solve the (TSP) problem and the application of the algorithm in conjun
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