TY - JOUR
T1 - Special issue on deep learning in image and video forensics
AU - Caldelli, Roberto
AU - Chaumont, Marc
AU - Li, Chang Tsun
AU - Amerini, Irene
PY - 2019/7
Y1 - 2019/7
N2 - The pervasiveness of new technologies, such as smartphones, tablets and Internet, makes digital images and videos the primary source of visual information in the modern day society. However, their reliability as a true representation of reality cannot be taken for granted due to the affordable powerful graphics editing software that can easily alter the original content without leaving noticeable visual trace of the modification. Nowadays, machine learning techniques and, in particular, Deep Learning have come to play a vital role in dealing with a massive amount of raw data. In recent years, deep neural networks, such as deep belief network, deep autoencoder and convolutional neural network (CNN), have shown to be capable of extracting complex statistical features and efficiently learning their representations, allowing it to generalize well across a wide variety of computer vision tasks, including image classification, speech recognition and so on.
AB - The pervasiveness of new technologies, such as smartphones, tablets and Internet, makes digital images and videos the primary source of visual information in the modern day society. However, their reliability as a true representation of reality cannot be taken for granted due to the affordable powerful graphics editing software that can easily alter the original content without leaving noticeable visual trace of the modification. Nowadays, machine learning techniques and, in particular, Deep Learning have come to play a vital role in dealing with a massive amount of raw data. In recent years, deep neural networks, such as deep belief network, deep autoencoder and convolutional neural network (CNN), have shown to be capable of extracting complex statistical features and efficiently learning their representations, allowing it to generalize well across a wide variety of computer vision tasks, including image classification, speech recognition and so on.
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U2 - 10.1016/j.image.2019.05.005
DO - 10.1016/j.image.2019.05.005
M3 - Editorial
AN - SCOPUS:85065601789
SN - 0923-5965
VL - 75
SP - 199
EP - 200
JO - Signal Processing: Image Communication
JF - Signal Processing: Image Communication
ER -