One of the most important food crops is rice. For this reason, accurate identification rice pests a critical foundation for pest control. In study, we propose an algorithm automatic and classification based on fully convolutional networks (FCNs) select 10 experiments. First, introduce new encoder–decoder in FCN series sub-networks connected by jump paths that combine long jumps shortcut connect...

The need for CT scan analysis is growing for pre-diagnosis and therapy of abdominal organs. Automatic organ segmentation of abdominal CT scan can help radiologists analyze the scans faster and segment organ images with fewer errors. However, existing methods are not efficient enough to perform the segmentation process for victims of accidents and emergencies situations. In this paper we propose...

In the supplementary material, we present the analysis of semantic boundary accurary in Section 1. In section 2, we evaluate the oracle performance on NYUDv2 40-class task with our spatio-temporal data-driven pooling. In section 3, we analyze the groundtruth annotations of the NYUDv2 40class task. In section 4, we provide the qualitative results of the semantic segmentation results of the NYUDv...

Molecular Field-Coupled Nanocomputing (FCN) is a computational paradigm promising high-frequency information elaboration at ambient temperature. This work proposes model to evaluate the signal energy involved in propagating and elaborating information. It splits evaluation into several contributions calculated with closed-form expressions without computationally expensive calculation. The essen...

The fully convolutional network (FCN) with an encoder-decoder architecture has been the standard paradigm for semantic segmentation. utilizes encoder to capture multilevel feature maps, which are incorporated into final prediction by a decoder. As context is crucial precise segmentation, tremendous effort made extract such information in intelligent fashion, including employing dilated/atrous c...

Obtaining the complete wear state of milling cutter during processing can help predict tool life and avoid impact breakage. A cylindrical model collection is proposed, which uses collected partial pictures side edge to construct a panoramic picture wear. After evaluating splicing accuracy, fully convolutional neural network (FCN) segmentation algorithm VGG16 structure used segment panorama end ...

Abstract Satellite image analysis is a research area in which many studies are carried out for civil and military applications the field of processing. imagery has including recognition, detection classification regions, buildings, roads, aircraft other man-made objects. Among these, especially strategically important applications, forms basis this study. In first phase study, new dataset aircr...

The fully convolutional network (FCN) has achieved tremendous success in dense visual recognition tasks, such as scene segmentation. last layer of FCN is typically a global classifier (1x1 convolution) to recognize each pixel semantic label. We empirically show that this classifier, ignoring the intra-class distinction, may lead sub-optimal results. In work, we present conditional replace tradi...

At present, most of the methods used in research image semantic segmentation ignore low-level feature information image, such as space, edge, etc., which leads to problems that edge and small part is not precise enough accuracy result high. To solve this problem, paper proposes a multi-source fusion model generative adversarial networks based on FCN: SCAGAN. In VGG19 network, add super-pixel de...