Speech synthesis (text-to-speech, TTS) and automatic speech recognition (ASR) are opposite tasks yet they can be complementary. In our work, we try to improve the TTS by using ASR. ASR plays the role of verifying the ...
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A cooperative intelligent transport system (C-ITS) enables information sharing among ITS subsystems, such as vehicle and roadside infrastructure, with vehicle-to-everything (V2X) communications. Novel C-ITS applicatio...
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In the current digital era, video surveillance has become a part of daily life. The person re-identification(re-ID) task involves choosing a person as a target in one camera feed and recognizing that target in footage...
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Alzheimer’s Disease(AD)is a progressive neurological *** diagnosis of this illness using conventional methods is very *** Learning(DL)is one of the finest solutions for improving diagnostic procedures’performance an...
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Alzheimer’s Disease(AD)is a progressive neurological *** diagnosis of this illness using conventional methods is very *** Learning(DL)is one of the finest solutions for improving diagnostic procedures’performance and forecast *** disease’s widespread distribution and elevated mortality rate demonstrate its significance in the older-onset and younger-onset age *** light of research investigations,it is vital to consider age as one of the key criteria when choosing the *** younger subjects are more susceptible to the perishable side than the older *** proposed investigation concentrated on the younger *** research used deep learning models and neuroimages to diagnose and categorize the disease at its early stages *** proposed work is executed in three *** 3D input images must first undergo image pre-processing using Weiner filtering and Contrast Limited Adaptive Histogram Equalization(CLAHE)*** Transfer Learning(TL)models extract features,which are subsequently compressed using cascaded Auto Encoders(AE).The final phase entails using a Deep Neural Network(DNN)to classify the phases of *** model was trained and tested to classify the five stages of *** ensemble ResNet-18 and sparse autoencoder with DNN model achieved an accuracy of 98.54%.The method is compared to state-of-the-art approaches to validate its efficacy and performance.
Corona virus(COVID-19)is once in a life time calamity that has resulted in thousands of deaths and security *** are using face masks on a regular basis to protect themselves and to help reduce corona virus *** the on-...
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Corona virus(COVID-19)is once in a life time calamity that has resulted in thousands of deaths and security *** are using face masks on a regular basis to protect themselves and to help reduce corona virus *** the on-going coronavirus outbreak,one of the major priorities for researchers is to discover effective *** important parts of the face are obscured,face identification and verification becomes exceedingly *** suggested method is a transfer learning using MobileNet V2 based technology that uses deep feature such as feature extraction and deep learning model,to identify the problem of face masked *** the first stage,we are applying face mask detector to identify the face ***,the proposed approach is applying to the datasets from Canadian Institute for Advanced Research10(CIFAR10),Modified National Institute of Standards and Technology Database(MNIST),Real World Masked Face Recognition Database(RMFRD),and Stimulated Masked Face Recognition Database(SMFRD).The proposed model is achieving recognition accuracy 99.82%with proposed *** article employs the four pre-programmed models VGG16,VGG19,ResNet50 and *** extract the deep features of faces with VGG16 is achieving 99.30%accuracy,VGG19 is achieving 99.54%accuracy,ResNet50 is achieving 78.70%accuracy and ResNet101 is achieving 98.64%accuracy with own *** comparative analysis shows,that our proposed model performs better result in all four previous existing *** fundamental contribution of this study is to monitor with face mask and without face mask to decreases the pace of corona virus and to detect persons using wearing face masks.
Graph convolutional networks (GCNs) have emerged as a powerful tool for action recognition, leveraging skeletal graphs to encapsulate human motion. Despite their efficacy, a significant challenge remains the dependenc...
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Video holds significance in computer graphics applications. Because of the heterogeneous of digital devices, retargeting videos becomes an essential function to enhance user viewing experience in such applications. In...
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India with its linguistic diversity consists of 22 officially recognized languages. The multilingual nation is shifting towards digitization which has brought an upsurge in identification of handwritten digits in regi...
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With the advancing technology, the increase in threats has been exponential. These technologies have led to the production of huge amounts of network traffic data. Therefore, it is of immense importance for the compan...
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In this paper, we improve the state-of-the-art ECAPA-TDNN model for speaker verification with CNN stem, self-calibration (SC) block, and deep layer aggregation. The proposed architecture is called Emphasized Channel A...
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