摘要 : By a News Reporter-Staff News Editor at Network Daily News – Fresh data onNetworks are presented in a new report. According to news reporting out of Jiangxi, People’s Republic ofChina, by NewsRx editors, research stated, “Current ... 展开 By a News Reporter-Staff News Editor at Network Daily News – Fresh data onNetworks are presented in a new report. According to news reporting out of Jiangxi, People’s Republic ofChina, by NewsRx editors, research stated, “Current top-performing saliency prediction methods of omnidirectionalimages (ODIs) depend on deep feedforward convolutional neural networks (CNNs), benefitingfrom their powerful multiscale representation ability. Although these methods adopt deep feedforwardCNNs to achieve superb performance in saliency prediction task, they have the following limitations: 1)these deep feedforward CNNs are difficult to map to ventral stream structure of the brain visual systemdue to their vast number of layers and missing biologically important connections, such as recurrence and2) most deep feedforward CNNs represent the multiscale features in a layerwise manner.” 收起