Generally, deep networks learn to recognize a category of objects by training on large number annotated images accurately. However, meta-learning problem known as low-shot image recognition task occurs when few with annotations are available for learning model single category. Consequently, the in testing/query and training/support datasets likely vary terms size, location, style, so on. In thi...

Convolutional Neural Network (CNN) has been widely applied in the field of synthetic aperture radar (SAR) image recognition. Nevertheless, CNN-based recognition methods usually encounter problem poor feature representation ability due to insufficient labeled SAR images. In addition, large inner-class variety and high cross-class similarity images pose a challenge for classification. To alleviat...

Widespread adoption of high-temperature polymer electrolyte membrane fuel cells (HT-PEMFCs) and HT-PEM electrochemical hydrogen pumps (HT-PEM ECHPs) requires models computational tools that provide accurate scale-up optimization. Knowledge-based modeling has limitations as it is time consuming information about the system not always available (e.g., material properties interfacial behavior betw...

BackgroundParkinson's disease (PD) is a heterogeneous condition. Cluster analysis based on cortical thickness has been used to define distinct patterns of brain atrophy in PD. However, the potential other neuroimaging modalities, such as white matter (WM) fractional anisotropy (FA), which also demonstrated be altered PD, not investigated.ObjectiveWe aim characterize PD subtypes using multimodal...

Abstract Data hallucination generates additional training examples for novel classes to alleviate the data scarcity problem in few‐shot learning (FSL). Existing hallucination‐based FSL methods normally train a general embedding model first by applying information extracted from base that have abundant data. In those methods, hallucinators are then built upon trained generate classes. However, t...

Smart agriculture is the application of modern information and communication technologies (ICT) to agriculture, leading what we might call a third green revolution. These include object detection classification such as plants, leaves, weeds, fruits well animals pests in agricultural domain. Object detection, one most fundamental difficult issues computer vision has attracted lot attention latel...