Over the years, Machine Translation in English to Punjabi has seen significant advancements. The study emphasizes Punjabi's unique linguistic complexities, which pose challenges for accurate and contextually relev...
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Emotion Recognition is a critical research area for enhancing human-computer interaction. Keystroke dynamics, a behavioral biometric capturing typing patterns, offers a non-intrusive, user-friendly method for recogniz...
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The Internet of Things(IoT)technologies has gained significant interest in the design of smart grids(SGs).The increasing amount of distributed generations,maturity of existing grid infrastructures,and demand network t...
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The Internet of Things(IoT)technologies has gained significant interest in the design of smart grids(SGs).The increasing amount of distributed generations,maturity of existing grid infrastructures,and demand network transformation have received maximum *** essential energy storing model mostly the electrical energy stored methods are developing as the diagnoses for its procedure was becoming further *** dynamic electrical energy stored model using Electric Vehicles(EVs)is comparatively standard because of its excellent electrical property and flexibility however the chance of damage to its battery was there in event of overcharging or deep discharging and its mass penetration deeply influences the *** paper offers a new Hybridization of Bacterial foraging optimization with Sparse Autoencoder(HBFOA-SAE)model for IoT Enabled energy *** proposed HBFOA-SAE model majorly intends to effectually estimate the state of charge(SOC)values in the IoT based energy *** accomplish this,the SAE technique was executed to proper determination of the SOC values in the energy ***,for improving the performance of the SOC estimation process,the HBFOA is *** addition,the HBFOA technique is derived by the integration of the hill climbing(HC)concepts with the BFOA to improve the overall *** ensuring better outcomes for the HBFOA-SAE model,a comprehensive set of simulations were performed and the outcomes are inspected under several *** experimental results reported the supremacy of the HBFOA-SAE model over the recent state of art approaches.
Smartphones are compatible and easily accessible compared to computers irrespective of place and time. Smartphones merge with our routine which acts as a medium of communication in several ways such as messaging, voic...
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Mental health challenges are growing in recent years, emphasizing the need for effective monitoring and inter- vention systems. This paper presents a comprehensive approach to detect mental unstabilities by analyzing ...
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Biometric characteristics are playing a vital role in security for the last few *** gait classification in video sequences is an important biometrics attribute and is used for security purposes.A new framework for hum...
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Biometric characteristics are playing a vital role in security for the last few *** gait classification in video sequences is an important biometrics attribute and is used for security purposes.A new framework for human gait classification in video sequences using deep learning(DL)fusion assisted and posterior probability-based moth flames optimization(MFO)is *** the first step,the video frames are resized and finetuned by two pre-trained lightweight DL models,EfficientNetB0 and *** models are selected based on the top-5 accuracy and less number of ***,both models are trained through deep transfer learning and extracted deep features fused using a voting *** the last step,the authors develop a posterior probabilitybased MFO feature selection algorithm to select the best *** selected features are classified using several supervised learning *** CASIA-B publicly available dataset has been employed for the experimental *** this dataset,the authors selected six angles such as 0°,18°,90°,108°,162°,and 180°and obtained an average accuracy of 96.9%,95.7%,86.8%,90.0%,95.1%,and 99.7%.Results demonstrate comparable improvement in accuracy and significantly minimize the computational time with recent state-of-the-art techniques.
作者：
Wang, Haozhe ZacWong, Yan TatMonash University
Department of Electrical and Computer Systems Engineering ClaytonVIC3800 Australia Monash University
Department of Electrical and Computer Systems Engineering Department of Physiology ClaytonVIC3800 Australia
Cortical visual prostheses can restore vision by directly stimulating the neurons in the visual cortex. The goal of these prostheses is to elicit sufficient light perception, known as phosphenes, to represent complex ...
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Image noise is undesirable that can negatively affect the quality of digital images. It reduces the image quality and increases the processing failure ratio. It is highly recommended to remove the noise, and before re...
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ISBN:
(纸本)9789819995615
Image noise is undesirable that can negatively affect the quality of digital images. It reduces the image quality and increases the processing failure ratio. It is highly recommended to remove the noise, and before removing the noise, we have to know the type of noise and estimate the parameters of noise for developing effective noise reduction techniques. This study introduces a method to effectively detect, recognize, and estimate image noise of various types (Gaussian, lognormal, Rayleigh, salt and pepper, and speckle). The proposed model consists of four stages: the first stage is detecting the noise in an image using a convolutional neural network. The second stage classifies the noisy images into one of five types of noise using a new method based on a combination of deep wavelets and support vector machines (SVM) classifier. The third stage involves estimating the parameters of the noise using maximum likelihood estimation (MLE). Finally, choosing the most suitable noise reduction technique for each type using linear and nonlinear filters and showing the capability of the suggested technique in estimating multiple noises commonly present in digital images. The proposed method utilizes a likelihood function derived from the MLE model for each noise type to estimate the noise parameters. Then used to select the most suitable noise reduction technique for each type. The quality of the denoised images is calculated utilizing the peak signal-to-noise ratio (PSNR) as the evaluation metric. The results show that the combination of wavelets with machine learning, specifically SVM, can highly enhance the results, where the accuracy was 93.043% through many experiments conducted to build a sturdy classification model. The MLE-based noise estimation method is also a reliable and accurate method for image noise estimation, especially for Gaussian, salt and pepper, lognormal, and Rayleigh noise. However, for highly noisy types such as speckle noise, further research is re
Modern optical technologies encompass classical light phenomena and non-linear effects, crucial for biomedical imaging and therapies. Despite substantial interest and many experimental studies, non-linear optical effe...
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