Electrophysiological recordings on the human scalp provide a wealth of information about
the temporal dynamics and nature of face perception at a global level of brain organization …

Deep learning with convolutional neural networks (deep ConvNets) has revolutionized
computer vision through end‐to‐end learning, that is, learning from the raw data. There is …

Deep learning methods, such as convolution neural networks (CNNs), have achieved
remarkable success in computer vision tasks. Hence, an increasing trend in using deep …

What if we could effectively read the mind and transfer human visual capabilities to computer
vision methods? In this paper, we aim at addressing this question by develo** the first …

Group decisions and even aggregation of multiple opinions lead to greater decision
accuracy, a phenomenon known as collective wisdom. Little is known about the neural basis …

The recognition of object categories is effortlessly accomplished in everyday life, yet its
neural underpinnings remain not fully understood. In this electroencephalography (EEG) …

Reading the human mind has been a hot topic in the last decades, and recent research in
neuroscience has found evidence on the possibility of decoding, from neuroimaging data …

Recent advancements in generative adversarial networks (GANs), using deep convolutional
models, have supported the development of image generation techniques able to reach …

Reconstructing images using brain signals of imagined visuals may provide an augmented
vision to the disabled, leading to the advancement of Brain-Computer Interface (BCI) …

Perceptual decision making is believed to be driven by the accumulation of sensory
evidence following stimulus encoding. More controversially, some studies report that neural …