While single-modal visible light images or infrared images provide limited information,infrared light captures significant thermal radiation data,whereas visible light excels in presenting detailed texture ***-bining ...
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While single-modal visible light images or infrared images provide limited information,infrared light captures significant thermal radiation data,whereas visible light excels in presenting detailed texture ***-bining images obtained from both modalities allows for leveraging their respective strengths and mitigating individual limitations,resulting in high-quality images with enhanced contrast and rich texture *** capabilities hold promising applications in advanced visual tasks including target detection,instance segmentation,military surveillance,pedestrian detection,among *** paper introduces a novel approach,a dual-branch decomposition fusion network based on AutoEncoder(AE),which decomposes multi-modal features into intensity and texture information for enhanced *** contrast enhancement module(CEM)and texture detail enhancement module(DEM)are devised to process the decomposed images,followed by image fusion through the *** proposed loss function ensures effective retention of key information from the source images of both *** comparisons and generalization experiments demonstrate the superior performance of our network in preserving pixel intensity distribution and retaining texture *** the qualitative results,we can see the advantages of fusion details and local *** the quantitative experiments,entropy(EN),mutual information(MI),structural similarity(SSIM)and other results have improved and exceeded the SOTA(State of the Art)model as a whole.
Millions of people die from lung illness each year as a result of its rise in recent years. CXR imaging is one of the most widely used and reasonably priced diagnostic techniques for the diagnosis of many illnesses. U...
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Millions of people die from lung illness each year as a result of its rise in recent years. CXR imaging is one of the most widely used and reasonably priced diagnostic techniques for the diagnosis of many illnesses. Unfortunately, even for seasoned radiologists, accurately diagnosing sickness from Chest X-Rays (CXR) samples is challenging. To combat the pandemic, a reliable, affordable, and efficient way to diagnose lung disease has become essential. Consequently, a unique optimized Auto Encod-BI Long-Short Term Memory (Bi-LSTM) model is proposed in this research work. Pre-processing, segmentation, feature extraction, and multiple types of lung illness diagnosis are the four main stages of the suggested model. First, Laplacian filtering and Contrast Limited Adaptive Histogram Equalization (CLAHE) are used to pre-process the gathered CXR pictures. Next, the Region of Interest (ROI) from the previously processed images are recognized by means of the newly enhanced MobileNetV2. The new Self-Improved Slime Mould Algorithm (SI-SMA) is used to fine-tune the hyper-parameters of MobileNetV2 in order to precisely identify the afflicted locations. Based on the phenomenon of slime mould oscillation, the conventional Slime Mould Algorithm (SMA) model has been modified with the creation of the SI-SMA model. Next, characteristics like the Local Binary Pattern (LBP) and Histogram of Oriented Gradient (HOG) are taken out. Finally, a unique AutoEncod-BiLSTM Framework—which is divided into three categories—is shown to automate the process of identifying illnesses in CXR pictures: pneumonia, COVID-19, and normal. The autoencoder and Bi-LSTM are combined to create the suggested AutoEncod-BiLSTM model. The retrieved features are used to train the AutoEncod-BiLSTM Framework. Moreover, the proposed model enhanced the disease detection efficiency than the existing models and the disease detection accuracy of the proposed model is about 99.1%. Furthermore, the suggested model attains better
Effective data communication is a crucial aspect of the Social Internet of Things(SIoT)and continues to be a significant research *** paper proposes a data forwarding algorithm based on Multidimensional Social Relatio...
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Effective data communication is a crucial aspect of the Social Internet of Things(SIoT)and continues to be a significant research *** paper proposes a data forwarding algorithm based on Multidimensional Social Relations(MSRR)in SIoT to solve this *** proposed algorithm separates message forwarding into intra-and cross-community forwarding by analyzing interest traits and social connections among *** new metrics are defined:the intensity of node social relationships,node activity,and community *** the community,messages are sent by determining which node is most similar to the sender by weighing the strength of social connections and node *** a node performs cross-community forwarding,the message is forwarded to the most reasonable relay community by measuring the node activity and the connection between *** proposed algorithm was compared to three existing routing algorithms in simulation *** indicate that the proposed algorithmsubstantially improves message delivery efficiency while lessening network overhead and enhancing connectivity and coordination in the SIoT context.
Machine Learning Research often involves the use of diverse libraries, modules, and pseudocodes for data processing, cleaning, filtering, pattern recognition, and computer intelligence. Quantization of Effort Required...
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Medical data mining has become an essential task in healthcare sector to secure the personal and medical data of patients using privacy *** this background,several authentication and accessibility issues emerge with a...
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Medical data mining has become an essential task in healthcare sector to secure the personal and medical data of patients using privacy *** this background,several authentication and accessibility issues emerge with an inten-tion to protect the sensitive details of the patients over getting published in open *** solve this problem,Multi Attribute Case based Privacy Preservation(MACPP)technique is proposed in this study to enhance the security of privacy-preserving *** information can be any attribute information which is categorized as sensitive logs in a patient’s *** semantic relation between transactional patient records and access rights is estimated based on the mean average value to distinguish sensitive and non-sensitive *** addition to this,crypto hidden policy is also applied here to encrypt the sensitive data through symmetric standard key log verification that protects the personalized sensitive ***,linear integrity verification provides authentication rights to verify the data,improves the performance of privacy preserving techni-que against intruders and assures high security in healthcare setting.
Deep learning is the subset of artificial intelligence and it is used for effective decision *** Sensor based automated irrigation system is proposed to monitor and cultivate *** system consists of Distributed wire-les...
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Deep learning is the subset of artificial intelligence and it is used for effective decision *** Sensor based automated irrigation system is proposed to monitor and cultivate *** system consists of Distributed wire-less sensor environment to handle the moisture of the soil and temperature *** is automated process and useful for minimizing the usage of resources such as water level,quality of the soil,fertilizer values and controlling the whole *** mobile app based smart control system is designed using deep belief *** system has multiple sensors placed in agriculturalfield and collect the *** collected transmitted to cloud server and deep learning process is applied for making *** residue analysis method is proposed for analyzing auto-mated and sensor captured ***,we used 512×512×3 layers deep belief network and 10000 trained data and 2500 test data are taken for *** is automated process once data is collected deep belief network is *** performance is compared with existing results and our process method has 94%of accuracy ***,our system has low cost and energy consumption also suitable for all kind of agriculturalfields.
Machine uptime is highly important as the repairing time takes longer which affects the production and the manufacturing industry focus on new ways of being competitive. Manufacturing and assembly parts of the machine...
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Link asymmetry in wireless mesh access networks(WMAN)of Mobile ad-hoc Networks(MANETs)is due mesh routers’transmission *** is depicted as significant research challenges that pose during the design of network protocol...
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Link asymmetry in wireless mesh access networks(WMAN)of Mobile ad-hoc Networks(MANETs)is due mesh routers’transmission *** is depicted as significant research challenges that pose during the design of network protocol in wireless *** on the extensive review,it is noted that the substantial link percentage is symmetric,i.e.,many links are *** is identified that the synchronous acknowledgement reliability is higher than the asynchronous ***,the process of establishing bidirectional link quality through asynchronous beacons underrates the link reliability of asym-metric *** paves the way to exploit an investigation on asymmetric links to enhance network functions through link ***,a novel Learning-based Dynamic Tree routing(LDTR)model is proposed to improve network performance and *** the evaluation of delay measures,asymmetric link,interference,probability of transmission failure is *** proportion of energy consumed is used for monitoring energy conditions based on the total energy *** learning model is a productive way for resolving the routing issues over the network model during *** asymmetric path is chosen to achieve exploitation and exploration *** learning-based Dynamic Tree routing model is utilized to resolve the multi-objective routing ***,the simulation is done with MATLAB 2020a simulation environment and path with energy-efficiency and lesser E2E delay is evaluated and compared with existing approaches like the Dyna-Q-network model(DQN),asymmetric MAC model(AMAC),and cooperative asymmetric MAC model(CAMAC)*** simulation outcomes demonstrate that the anticipated LDTR model attains superior network performance compared to *** average energy consump-tion is 250 J,packet energy consumption is 6.5 J,PRR is 50 bits/sec,95%PDR,average delay percentage is 20%.
Interoperability is a crucial aspect of the effective functioning of Internet of Things (IoT) devices, particularly in the healthcare industry. Although the use of IoT devices in healthcare has brought numerous benefi...
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One of the crucial approaches that use tracking and analyzing human movement for the identification of functional disorders and illnesses of the human body is known as the gait analysis method. This method helps diagn...
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