This paper explores how well deep learning models trained on chest CT images can diagnose COVID-19 infected people in a fast and automated process. To this end, we adopted advanced network architectures proposed transfer strategy using custom-sized input tailored for each architecture to achieve the best performance. We conducted extensive sets of experiments two image datasets, namely, SARS-CoV-2 CT-scan COVID19-CT. The results show superior performances our compared with previous studies....

Diabetic retinopathy (DR) is a diabetes complication that affects the eye and can cause damage from mild vision problems to complete blindness. It has been observed fundus images show various kinds of color aberrations irrelevant illuminations, which degrade diagnostic analysis may hinder results. In this research, we present methodology eliminate these unnecessary reflectance properties using novel image processing schema stacked deep learning technique for diagnosis. For luminosity...

The recognition performance of visual systems is highly dependent on extracting and representing the discriminative characteristics image data. Convolutional neural networks (CNNs) have shown unprecedented success in a variety tasks due to their capability provide in-depth representations exploiting features appearance, color, texture. This paper presents novel system for ear based ensembles deep CNN-based models more specifically Visual Geometry Group (VGG)-like network architectures from...

The COVID-19 pandemic has caused drastic changes across the globe, affecting all areas of life. This paper provides a comprehensive study on influence in various fields such as economy, education, society, environment, and globalization. In this study, both positive negative consequences education are studied. Modern technologies combined with conventional teaching to improve communication between instructors learners. also greatly affected people disabilities those who older, these persons...

Quality-of-service (QoS) is the term used to evaluate overall performance of a service. In healthcare applications, efficient computation QoS one mandatory requirements during processing medical records through smart measurement methods. Medical services often involve transmission demanding information. Thus, there are stringent for secure, intelligent, public-network quality-of-service. This paper contributes three different aspects. First, we propose novel metaheuristic approach...

Brain tumors are the most common and aggressive illness, with a relatively short life expectancy in their severe form. Thus, treatment planning is an important step improving patients’ quality of life. In general, image methods such as computed tomography (CT), magnetic resonance imaging (MRI), ultrasound images used to assess brain, lung, liver, breast, prostate, so on. X‐ray images, particular, utilized this study diagnose brain tumors. This paper describes investigation convolutional...

Degree attestation verification and traceability are complex one-to-one processes between the Higher Education Commission (HEC) universities. The procedure shifted to digitalized manner, but still, on a certain note, manual authentication is required. In initial process, university verified degree stamp seal first. Then, physical channel of submission receiving ends activated. After that, attested while properly examining analyzing tamper records related credentials through e-communication...

The detection of the objects in ariel image has a significant impact on field parking space management, traffic management activities and surveillance systems. Traditional vehicle algorithms have some limitations as these are not working with complex background small size object bigger scenes. It is observed that researchers facing numerous problems classification, i.e., complicated background, vehicle’s modest size, other similar visual appearances correctly addressed. A robust algorithm...

Early detection of brain tumors can save precious human life. This work presents a fully automated design to classify tumors. The proposed scheme employs optimal deep learning features for the classification FLAIR, T1, T2, and T1CE Initially, we normalized dataset pass them ResNet101 pretrained model perform transfer our dataset. approach results in fine-tuning tumor classification. problem with this is generation redundant features. These degrade accuracy cause computational overhead. To...

Coronavirus disease (COVID-19) is a viral infection caused by SARS-CoV-2. The modalities such as computed tomography (CT) have been successfully utilized for the early stage diagnosis of COVID-19 infected patients. Recently, many researchers deep learning models automated screening suspected cases. An ensemble and Internet Things (IoT) based framework proposed Three well-known pretrained are ensembled. medical IoT devices to collect CT scans, diagnoses performed on servers. compared with...

This paper employs state-of-the-art Deep Convolutional Neural Networks (CNNs), namely AlexNet, VGGNet, Inception, ResNet and ResNeXt in a first experimental study of ear recognition on the unconstrained EarVN1.0 dataset. As dataset size is still insufficient to train deep CNNs from scratch, we utilize transfer learning propose different domain adaptation strategies. The experiments show that our networks, which are fine-tuned using custom-sized inputs determined specifically for each CNN...

Ear recognition is an active research area in the biometrics community with ultimate goal to recognize individuals effectively from ear images. Traditional methods based on handcrafted features and conventional machine learning classifiers were prominent techniques during last two decades. Arguably, feature extraction crucial phase for success of these due difficulty designing robust cope variations given Currently, shifting towards extracted by Convolutional Neural Networks (CNNs), which...

Accurate and early detection of machine faults is an important step in the preventive maintenance industrial enterprises. It essential to avoid unexpected downtime as well ensure reliability equipment safety humans. In case rotating machines, significant information about machine's health condition present spectrum its vibration signal. This work proposes a fault system machines using signal analysis. First, dataset 3-dimensional signals acquired from large induction motors representing...

Software-defined network (SDN) becomes a new revolutionary paradigm in networks because it provides more control and operation over infrastructure. The SDN controller is considered as the operating system of based infrastructure, responsible for executing different applications maintaining services functionalities. Despite all its tremendous capabilities, face many security issues due to complexity architecture. Distributed denial (DDoS) common attack on centralized architecture, especially...

In this paper we propose two novel deep convolutional network architectures, CovidResNet and CovidDenseNet, to diagnose COVID-19 based on CT images. The models enable transfer learning between different which might significantly boost the diagnostic performance. Whereas architectures usually suffer from lack of pretrained weights, our proposed can be partly initialized with larger baseline like ResNet50 DenseNet121, is attractive because abundance public repositories. are utilized in a first...

Coronavirus disease 2019 (COVID-19) is a highly contagious that has claimed the lives of millions people worldwide in last 2 years. Because disease's rapid spread, it critical to diagnose at an early stage order reduce rate spread. The images lungs are used this infection. In years, many studies have been introduced help with diagnosis COVID-19 from chest X-Ray images. all researchers looking for quick method virus, deep learning-based computer controlled techniques more suitable as second...

The COVID-19 virus's rapid global spread has caused millions of illnesses and deaths. As a result, it disastrous consequences for people's lives, public health, the economy. Clinical studies have revealed link between severity cases amount virus present in infected lungs. Imaging techniques such as computed tomography (CT) chest x-rays can detect (CXR). Manual inspection these images is difficult process, so computerized are widely used. Deep convolutional neural networks (DCNNs) type...

Network on chip (NoC) is an integrated communication system (SoC), efficiently connecting various intellectual property (IP) modules a single die. NoC has been suggested as enormously scalable solution to overcome the problems in SoC. The performance of depends several aspects terms area, latency, throughput, and power. In this paper, 2D 3D mesh Virtex-5 field-programmable gate array (FPGA) studied. design carried Xilinx ISE 14.7 behavior model followed based XY XYZ routing for respectively....

This paper presents ear recognition models constructed with Deep Residual Networks (ResNet) of various depths. Due to relatively limited amounts images we propose three different transfer learning strategies address the problem. is done either through utilizing ResNet architectures as feature extractors or employing end-to-end system designs. First, use pretrained trained on specific visual tasks, inititalize network weights and train fully-connected layer task. Second, fine-tune entire...

The network-on-chip (NoC) technology is frequently referred to as a front-end solution back-end problem. physical substructure that transfers data on the chip and ensures quality of service begins collapse when size semiconductor transistor dimensions shrinks growing numbers intellectual property (IP) blocks working together are integrated into chip. system (SoC) architecture today so complex not utilizing crossbar traditional hierarchical bus architecture. NoC connectivity reduces amount...

Seagull Optimization Algorithm (SOA) is a metaheuristic algorithm that mimics the migrating and hunting behaviour of seagulls. SOA able to solve continuous real-life problems, but not discrete problems. The eight different binary versions are proposed in this paper. uses four transfer functions, S-shaped V-shaped, which used map search space into space. Twenty-five benchmark functions validate performance algorithm. statistical significance also analysed. Experimental results divulge...