Semantic labeling is an active field in remote sensing applications. Although handling high detailed objects in Very High Resolution (VHR) optical image and VHR Digital Surface Model (DSM) is a challenging task, it can improve the accuracy of semantic labeling methods. In this paper, a semantic labeling method is proposed by fusion of optical and normalized DSM data. Spectral and spatial featur...

Machine learning models have demonstrated vulnerability to adversarial attacks, more specifically misclassification of examples. In this article, we propose a one-off and attack-agnostic Feature Manipulation (FM)-Defense detect purify examples in an interpretable efficient manner. The intuition is that the classification result normal image generally resistant non-significant intrinsic feature ...

Deep neural networks have been shown to be vulnerable adversarial attacks that perturb inputs based on semantic features. Existing robustness analyzers can reason about feature neighborhoods increase the networks’ reliability. However, despite significant progress in these techniques, they still struggle scale deep and large neighborhoods. In this work, we introduce VeeP, an active learning app...

Memory and language are important high-level cognitive functions of humans, the study conceptual representation human brain is a key approach to reveal principles cognition. However, this research often constrained by availability stimulus materials. The on concept needs be based standardized large-scale database semantic features. Although Western scholars have established variety English feat...

the persian morpheme ra has attracted the attention of many linguists including karimi (1989), dabir-moghaddam (1990) and ghomeshi (1996) among others. karimi takes ra as the accusative case marker, the presence of which on subjects and objects of prepositions render the sentence ungrammatical. according to ghomeshi (1996), it marks dps functioning as vp-level topics. dabir-moghaddam (1990) ana...