Akshay Nayak - Academia.edu (original) (raw)

Akshay Nayak

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Papers by Akshay Nayak

Research paper thumbnail of Forged File Detection and Steganographic content Identification (FFDASCI) using Deep Learning Techniques

This paper presents our contribution in the identification and detection of Forged files and Steg... more This paper presents our contribution in the identification and detection of Forged files and Steganographic content using Deep Neural Networks like Convolutional Neural Network and 3D-RESNET. We have used CNN in our research as CNN’s are inspired by visual cortex. In other words, they are designed to extract consequential features which are relevant in classification i.e. the ones which minimizes the loss function. In this the kernel weights are learned by Gradient Descent so as to generate the perceptive features from images fed to the network which in result supplemented to fully connected layer that performs the final classification task. In our proposed approach we mainly consider the two different tasks. Firstly, Identification of Forged Images has been carried out in which detection of altered images which includes both extension and signature has been performed. In addition to this, we have predicted the original epitome of forged file by using convolutional neural network mo...

Research paper thumbnail of Facial Expression Recognition Using Fusion of Deep Learning and Multiple Features

Machine Learning Algorithms and Applications, 2021

Research paper thumbnail of INASNET: Automatic identification of coronavirus disease (COVID-19) based on chest X-ray using deep neural network

Research paper thumbnail of INASNET: Automatic identification of coronavirus disease (COVID-19) based on chest X-ray using deep neural network

Research paper thumbnail of Forged File Detection and Steganographic content Identification (FFDASCI) using Deep Learning Techniques

This paper presents our contribution in the identification and detection of Forged files and Steg... more This paper presents our contribution in the identification and detection of Forged files and Steganographic content using Deep Neural Networks like Convolutional Neural Network and 3D-RESNET. We have used CNN in our research as CNN’s are inspired by visual cortex. In other words, they are designed to extract consequential features which are relevant in classification i.e. the ones which minimizes the loss function. In this the kernel weights are learned by Gradient Descent so as to generate the perceptive features from images fed to the network which in result supplemented to fully connected layer that performs the final classification task. In our proposed approach we mainly consider the two different tasks. Firstly, Identification of Forged Images has been carried out in which detection of altered images which includes both extension and signature has been performed. In addition to this, we have predicted the original epitome of forged file by using convolutional neural network mo...

Research paper thumbnail of Facial Expression Recognition Using Fusion of Deep Learning and Multiple Features

Machine Learning Algorithms and Applications, 2021

Research paper thumbnail of INASNET: Automatic identification of coronavirus disease (COVID-19) based on chest X-ray using deep neural network

Research paper thumbnail of INASNET: Automatic identification of coronavirus disease (COVID-19) based on chest X-ray using deep neural network

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