… Abstract: Fruit recognition and segmentation using deep neural networks have widely
been contributed to the operation of picking robots in modern agriculture. However, the most …

… Multiscale brain MRI super-resolution using deep 3D convolutional networks[J]. Co…
Enhanced deep residual networks for single image super-resolution[C] //Proceedings of the IEEE …

… through a single network due to its multi-shapes, directions and densities.We present a
single image rain removal method based on multi scale progressive residual network (MSPRNet)…

… To address this problem, we propose a novel generative adversarial network (GAN) for
image super-resolution combining perceptual loss to further improve SR performance. This …

… This paper proposed an automatic recognition algorithm of lactating sow postures based
on improved Faster R-CNN (convolutional neural network) using depth video images. To …

… A unified multi-scale deep convolutional neural network for fast object detection [C]//
Proceedings of IEEE European Conference on Computer Vision,Cham:Springer,2016:354-370. [20] …

… on the edge information of lowdose CT images and fully utilize the edge information to
preserve the structures. In order to make full use of the encoder features, this paper introduces the …

… image registration. Compared with the conventional methods, the deep learning methods for
medical image … paper divides the deep learning methods for medical image registration into …