Mc-DNN
نویسندگان
چکیده
With the advancement of technology, social media has become a major source digital news due to its global exposure. This led an increase in spreading fake and misinformation online. Humans cannot differentiate from real because they can be easily influenced. A lot research work been conducted for detecting using Artificial Intelligence Machine Learning. large number deep learning models their architectural variants have investigated many websites are utilizing these directly or indirectly detect news. However, state-of-the-arts demonstrate limited accuracy distinguishing original We propose multi-channel model namely Mc-DNN, leveraging processing headlines articles along different channels differentiating achieve highest 99.23% on ISOT Fake News Dataset 94.68% Data Mc-DNN. Thus, we highly recommend use Mc-DNN detection.
منابع مشابه
DNN-Train: Benchmarking and Analyzing DNN Training
We aim to build a new benchmark pool for deep neural network training and to analyze how eicient existing frameworks are in performing this training. We will provide our methodology and develop proper proiling tools to perform this analysis.
متن کاملDNN-based uncertainty estimation for weighted DNN-HMM ASR
In this paper, the uncertainty is defined as the mean square error between a given enhanced noisy observation vector and the corresponding clean one. Then, a DNN is trained by using enhanced noisy observation vectors as input and the uncertainty as output with a training database. In testing, the DNN receives an enhanced noisy observation vector and delivers the estimated uncertainty. This unce...
متن کاملDNN Flow: DNN Feature Pyramid based Image Matching
Figure 1: Matching I1 and I2 using DNN flow. Each column shows the matching of different levels. In first row, parallelogram denotes the DNN feature image of I1, where dot represents the feature at that location. Line with arrow denotes the flow vector of the corresponding feature, while curve with arrow denotes guidance from high level to low level. In second row, the color rectangles show I1’...
متن کاملGmm-free Dnn Training
While deep neural networks (DNNs) have become the dominant acoustic model (AM) for speech recognition systems, they are still dependent on Gaussian mixture models (GMMs) for alignments both for supervised training and for context dependent (CD) tree building. Here we explore bootstrapping DNN AM training without GMM AMs and show that CD trees can be built with DNN alignments which are better ma...
متن کاملDeepWarp: DNN-based Nonlinear Deformation
DeepWarp is an efficient and highly re-usable deep neural network (DNN) based nonlinear deformable simulation framework. Unlike other deep learning applications such as image recognition, where different inputs have a uniform and consistent format (e.g. an array of all the pixels in an image), the input for deformable simulation is quite variable, high-dimensional, and parametrization-unfriendl...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal on Semantic Web and Information Systems
سال: 2022
ISSN: ['1552-6291', '1552-6283']
DOI: https://doi.org/10.4018/ijswis.295553