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Bengaluru-based neuroscientists have trained macaque monkeys to carry out complex cerebral tasks on a touchscreen while placed inside a room, opening a new window to study animal behaviour and cognition. ....
BENGALURU: A new study from IISc’s Centre for Neuroscience (CNS) has explored how well deep neural networks machine learning systems inspired by the network of brain cells or neurons in the human brain compare to the human brain when it comes to visual perception. Pointing out that deep neural networks can be trained to perform specific tasks, researchers say that they have played a pivotal role in helping scientists understand how our brains perceive the things that we see. “Although deep networks have evolved significantly over the past decade, they are still nowhere close to performing as well as the human brain in perceiving visual cues. In a recent study, SP Arun, associate professor at CNS, and his team have compared various qualitative properties of these deep networks with those of the human brain,” IISc said in a statement. ....
Highlights Researchers compared visual perception of deep neural networks to that of humans Deep networks exhibited similarities and dissimilarities from human brain New Delhi: Deep neural networks – a technology which has been in the works for over a decade and provides crucial insights into how human beings perceive things – evolved a bit further as researchers found some fascinating new facts. A team of researchers at the Centre for Neuroscience (CNS) at the Indian Institute of Science (IISc) recently conducted a study to compare the visual perception of the deep neural networks to that of humans. They found that the deep networks are capable of seeing the very objects humans see, they just see it ‘differently’. ....
Image for representational purpose (Pic: PTI) Researchers from the Indian Institute of Science (IISc) in their study have found crucial qualitative differences between the human brain and Deep Neural Networks, and these gaps can be filled by training the deep networks on larger datasets, incorporating more constraints or by modifying network architecture. The team from the Centre for Neuroscience (CNS) studied 13 different perceptual effects and found that Convolutional or deep neural networks that have their object representations match coarsely with the brain are still outperformed by humans. Lots of studies have been showing similarities between deep networks and brains, but no one has really looked at systematic differences, said SP Arun, Associate Professor at CNS and senior author of the study in a note by the institute. Identifying these differences can push us closer to making these networks more brain-like, he added. ....
New study explores deep neural networks' visual perception thehindu.com - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from thehindu.com Daily Mail and Mail on Sunday newspapers.