this research aims to introduce culture and thought -within whorfian hypothesis-of the target language to efl learners and helps them get a deeper idea over the root and reference of words and thereby keep them longer in memory. to test the hypothesis orwell’s animal farm was chosen along with two translations in persian as well as a persian short story titled ahu-ye kuhi . required data were e...

Due to the increasing web, there are many challenges to establish a general framework for data mining and retrieving structured data from the Web. Creating an ontology is a step towards solving this problem. The ontology raises the main entity and the concept of any data in data mining. In this paper, we tried to propose a method for applying the "meaning" of the search system, But the problem ...

Mixup provides interpolated training samples and allows the model to obtain smoother decision boundaries for better generalization. The idea can be naturally applied domain adaptation task, where we mix source target domain-mixed adaptation. However, extension of from classification segmentation (i.e., structured output) is nontrivial. This paper systematically studies impact mixup under adapti...

Domain adaptive semantic segmentation attempts to make satisfactory dense predictions on an unlabeled target domain by utilizing the supervised model trained a labeled source domain. One popular solution is self-training, which retrains with pseudo labels instances. Plenty of approaches tend alleviate noisy labels, however, they ignore intrinsic connection training data, i.e., intra-class compa...

Content-based image retrieval and text-based image retrieval are two fundamental approaches in the field of image retrieval. The challenges related to each of these approaches, guide the researchers to use combining approaches and semi-automatic retrieval using the user interaction in the retrieval cycle. Hence, in this paper, an image retrieval system is introduced that provided two kind of qu...

Existing techniques to adapt semantic segmentation networks across source and target domains within deep convolutional neural (CNNs) deal with all the samples from two in a global or category-aware manner. They do not consider an inter-class variation domain itself estimated category, providing limitation encode having multi-modal data distribution. To overcome this limitation, we introduce lea...

we deal with a wide range of colors in our daily life. they are such ubiquitous phenomena that is hard and next to impossible to imagine even a single entity (be it an object, place, living creature, etc) devoid of them. they are like death and tax which nobody can dispense with. this omnipresence of colors around us has also made its way through abstract and less tangible entities via the inte...

Scene segmentation is widely used in autonomous driving for environmental perception. Semantic scene (3S) has gained considerable attention owing to its rich semantic information. It assigns labels the pixels an image, thereby enabling automatic image labeling. Current approaches are based mainly on convolutional neural networks (CNN), however, they rely numerous labels. Therefore, use of a sma...