Deep learning-based approaches are applied successfully in manyfields such as deepFake identification,big data analysis,voice recognition,and image recognition.Deepfake is the combination of deep learning in fake creati...Deep learning-based approaches are applied successfully in manyfields such as deepFake identification,big data analysis,voice recognition,and image recognition.Deepfake is the combination of deep learning in fake creation,which states creating a fake image or video with the help of artificial intelligence for political abuse,spreading false information,and pornography.The artificial intel-ligence technique has a wide demand,increasing the problems related to privacy,security,and ethics.This paper has analyzed the features related to the computer vision of digital content to determine its integrity.This method has checked the computer vision features of the image frames using the fuzzy clustering feature extraction method.By the proposed deep belief network with loss handling,the manipulation of video/image is found by means of a pairwise learning approach.This proposed approach has improved the accuracy of the detection rate by 98%on various datasets.展开更多
Approximation space can be said to play a critical role in the accuracy of the set’s approximations.The idea of“approximation space”was introduced by Pawlak in 1982 as a core to describe information or knowledge in...Approximation space can be said to play a critical role in the accuracy of the set’s approximations.The idea of“approximation space”was introduced by Pawlak in 1982 as a core to describe information or knowledge induced from the relationships between objects of the universe.The main objective of this paper is to create new types of rough set models through the use of different neighborhoods generated by a binary relation.New approximations are proposed representing an extension of Pawlak’s rough sets and some of their generalizations,where the precision of these approximations is substantially improved.To elucidate the effectiveness of our approaches,we provide some comparisons between the proposed methods and the previous ones.Finally,we give a medical application of lung cancer disease as well as provide an algorithm which is tested on the basis of hypothetical data in order to compare it with current methods.展开更多
文摘Deep learning-based approaches are applied successfully in manyfields such as deepFake identification,big data analysis,voice recognition,and image recognition.Deepfake is the combination of deep learning in fake creation,which states creating a fake image or video with the help of artificial intelligence for political abuse,spreading false information,and pornography.The artificial intel-ligence technique has a wide demand,increasing the problems related to privacy,security,and ethics.This paper has analyzed the features related to the computer vision of digital content to determine its integrity.This method has checked the computer vision features of the image frames using the fuzzy clustering feature extraction method.By the proposed deep belief network with loss handling,the manipulation of video/image is found by means of a pairwise learning approach.This proposed approach has improved the accuracy of the detection rate by 98%on various datasets.
文摘Approximation space can be said to play a critical role in the accuracy of the set’s approximations.The idea of“approximation space”was introduced by Pawlak in 1982 as a core to describe information or knowledge induced from the relationships between objects of the universe.The main objective of this paper is to create new types of rough set models through the use of different neighborhoods generated by a binary relation.New approximations are proposed representing an extension of Pawlak’s rough sets and some of their generalizations,where the precision of these approximations is substantially improved.To elucidate the effectiveness of our approaches,we provide some comparisons between the proposed methods and the previous ones.Finally,we give a medical application of lung cancer disease as well as provide an algorithm which is tested on the basis of hypothetical data in order to compare it with current methods.
