Results 11 to 20 of about 39,255 (224)
Current Directions in Biomedical Engineering, 2023 Real time physiological signals like Electrodermal Activity (EDA), measured using wearable devices, could be used for emotion recognition, thus enabling new paradigms of health monitoring, including mental health.
Anthiyur Aravindan Abhinav +3 more
doaj +1 more source
Waste material classification using performance evaluation of deep learning models
Journal of Intelligent Systems, 2023 Waste classification is the issue of sorting rubbish into valuable categories for efficient waste management. Problems arise from issues such as individual ignorance or inactivity and more overt issues like pollution in the environment, lack of resources,
Al-Mashhadani Israa Badr
doaj +1 more source
Sakarya University Journal of Computer and Information Sciences, 2022 Physical layer authentication is an important technique for cybersecurity, especially in military scenarios. Device classification using radio frequency fingerprinting, which is based on recognizing device-unique characteristics of the transient waveform
Özkan Yılmaz, Mehmet Akif Yazıcı
doaj +1 more source
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), 2022 Based on the WHO Report related to malaria, it is estimated that there will be 241 million malaria cases and 627,000 deaths from this disease globally in 2020 with the number of deaths increasing yearly.
Aris Muhandisin, Yufis Azhar
doaj +1 more source
A Hybrid Approach for Landmark Recognition using Deep Local Features and Residual Network-50 [PDF]
ITM Web of Conferences, 2021 As smartphones and mobile data become universal in modern society, the opportunities to interact with the real world would grow tremendously. Latest Technologies such as Oculus Rift and Google Glass attempt to bridge the gap between the virtual and the ...
Nimbare Nishant +3 more
doaj +1 more source
智能科学与技术学报, 2021 针对皮肤镜图像数量不充足以及各类疾病之间影像数据不平衡的问题，提出一种融合类加权交叉熵损失函数和分层卷积神经网络的皮肤镜图像分类方法。首先对皮肤镜图像进行色彩恒常化处理，消除环境光源噪声；然后构建基于ResNet 50的分层卷积神经网络，并在迁移学习的基础上分别构建二分类和多分类卷积神经网络模型，根据皮肤镜图像的数量特点设置类加权交叉熵损失函数。实验结果表明，该方法具有较好的分类效果，分类准确率达到了85.94%，与未改进的分类模型ResNet 50相比，测试准确率提高了5.752%。
邵虹, 张鸣坤, 崔文成
doaj
Image-based skin disease detection: Psoriasis, Eczema, and Acne using VGG16 and ResNet-50 [PDF]
EPJ Web of ConferencesMillions of people around the world are affected by skin diseases, which represent a serious health risk. For these illnesses to be effectively treated, a timely and precise diagnosis is essential. This project uses deep learning techniques, specifically
Kumbhar Aditi +4 more
doaj +1 more source
Cervix Image Classification for Prognosis of Cervical Cancer using Deep Neural Network with Transfer Learning [PDF]
EAI Endorsed Transactions on Pervasive Health and Technology, 2021 INTRODUCTION: Cervical cancer is the leading cancer among the other female cancers. It develops in the cervix of women. It takes decades in development thus can be preventable if diagnosed at an early stage. The cervix is classified into three types Type
Sanjeev Dhawan +2 more
doaj +1 more source
Heston‐GA Hybrid Option Pricing Model Based on ResNet50
Discrete Dynamics in Nature and Society, 2022 (1) Background. This study aims to improve the accuracy of the pricing model. (2) Methods. Heston model is combined with ResNet50 convolutional neural network model. Based on the optimization of Heston model parameters by genetic algorithm (GA), ResNet50 model is used to correct the deviation between market option price and Heston price, so a new ...
Zheng Yang +3 more
openaire +3 more sources