Unsupervised learning with generative adversarial networks (GANs) has proven hugely successful. Regular GANs hypothesize the discriminator as a classifier sigmoid cross entropy loss function. However, we found that this function may lead to vanishing gradients problem during process. To overcome such problem, propose in paper Least Squares Generative Adversarial Networks (LSGANs) which adopt least squares for discriminator. We show minimizing objective of LSGAN yields Pearson X2 divergence....

The rapid advancement of computing technologies has facilitated the implementation AIED (Artificial Intelligence in Education) applications. refers to use AI Intelligence) or application programs educational settings facilitate teaching, learning, decision making. With help technologies, which simulate human intelligence make inferences, judgments, predictions, computer systems can provide personalized guidance, supports, feedback students as well assisting teachers policymakers making...

Considering the increasing importance of Artificial Intelligence in Education (AIEd) and absence a comprehensive review on it, this research aims to conduct systematic influential AIEd studies. We analyzed 45 articles terms annual distribution, leading journals, institutions, countries/regions, most frequently used terms, as well theories technologies adopted. also evaluated definitions from broad narrow perspectives clarified relationship among AIEd, Educational Data Mining, Computer-Based...

Computers & Education has been leading the field of computers in education for over 40 years, during which time it developed into a well-known journal with significant influences on educational technology research community. Questions such as "in what topics were academic community interested?" "how did evolve time?" and "what main concerns its major contributors?" are important to both editorial board readership Education. To address these issues, this paper conducted structural topic...

Given the importance of word knowledge for second language acquisition, there is always a need effective word-learning approaches from learners. With rapid development educational technologies, game-based learning emerging into field with considerable potential, within which, digital vocabulary has accrued increasing attention learners, educators and researchers. The present research reviews studies on five perspectives: general overview published studies, games learning, theoretical...

Unsupervised learning with generative adversarial networks (GANs) has proven to be hugely successful. Regular GANs hypothesize the discriminator as a classifier sigmoid cross entropy loss function. However, we found that this function may lead vanishing gradients problem during process. To overcome such problem, propose in paper Least Squares Generative Adversarial Networks (LSGANs) which adopt least squares for both and generator. We show minimizing objective of LSGAN yields Pearson χ2...

This paper looks at this intriguing question: are single images with their details lost during deraining, reversible to artifact-free status? We propose an end-to-end detail-recovery image deraining network (termed a DRDNet) solve the problem. Unlike existing approaches that attempt meet conflicting goal of simultaneously and preserving in unified framework, we view rain removal detail recovery as two seperate tasks, so each part could specialize rather than trade-off between goals....

With the rapid development of artificial intelligence (AI) technologies and a continuously growing interest in their application educational contexts, there has been significant growth scientific literature relation to AI education (AIEd). This study aims present multiple perspectives on AIEd terms relevant grants, conferences, journals, software tools, article trends, top issues, institutions, researchers provide an overview for its further implementation. this study, we contribute research...

Abstract Innovative information and communication technologies have reformed higher education from the traditional way to smart learning. Smart learning applies technological social developments facilitates effective personalized with innovative technologies, especially devices online technologies. has attracted increasing research interest academia. This study aims comprehensively review field of by conducting a topic modeling analysis 555 publications collected Scopus database. In...

Abstract The British Journal of Educational Technology (BJET) has been active in the field educational technology since 1970. To celebrate its 50th anniversary and to demonstrate a comprehensive overview field, we conducted bibliometric analysis 3710 publications this journal from 1971 2018 as indexed Web Science with full bibliographic information. This study aimed (1) identify publication citation trends, (2) explore distribution paper types, (3) recognize most relevant countries/regions,...

Can you find me? By simulating how humans to discover the so-called 'perfectly'-camouflaged object, we present a novel boundary-guided separated attention network (call BSA-Net). Beyond existing camouflaged object detection (COD) wisdom, BSA-Net utilizes two-stream modules highlight separator (or say object's boundary) between an image's background and foreground: reverse stream helps erase interior focus on background, while normal recovers thus pay more foreground; both streams are...

Sentiment analysis AKA opinion mining is one of the most widely used NLP applications to identify human intentions from their reviews. In education sector, listen student opinions and enhance learning–teaching practices pedagogically. With advancements in sentiment annotation techniques AI methodologies, comments can be labelled with orientation without much intervention.​ this review article, (1) we consider role emotional four levels: document level, sentence entity aspect (2) including...

Research on Educational Metaverse (Edu-Metaverse) has developed into an active research field. Based 310 academic papers published from 2004 to 2022, this study identifies contributors, scientific cooperations, and themes using bibliometrics, social network analysis, topic modeling, keyword analysis. Results suggest that Edu-Metaverse gained increasing attention in academia since 2019. Countries/affiliations located the same regions are close partners cooperation. By jointly interpreting...

Multimodal medical data fusion has emerged as a transformative approach in smart healthcare, enabling comprehensive understanding of patient health and personalized treatment plans. In this paper, journey from to information knowledge wisdom (DIKW) is explored through multimodal for healthcare. We present review focused on the integration various modalities. The explores different approaches such feature selection, rule-based systems, machine ;earning, deep learning, natural language...

While the wisdom of training an image dehazing model on synthetic hazy data can alleviate difficulty collecting real-world hazy/clean pairs, it brings well-known domain shift problem. From a different yet new perspective, this paper explores contrastive learning with adversarial effort to leverage unpaired and clean images, thus alleviating problem enhancing network's generalization ability in scenarios. We propose effective unsupervised paradigm for dehazing, dubbed UCL-Dehaze. Unpaired...

Abstract Advancements in artificial intelligence (AI) have driven extensive research into developing diverse multimodal data analysis approaches for smart healthcare. There is a scarcity of large-scale literature this field based on quantitative approaches. This study performed bibliometric and topic modeling examination 683 articles from 2002 to 2022, focusing topics trends, journals, countries/regions, institutions, authors, scientific collaborations. Results showed that, firstly, the...

The classification of remote sensing images is inherently challenging due to the complexity, diversity, and sparsity data across different image samples. Existing advanced methods often require substantial modifications model architectures achieve optimal performance, resulting in complex frameworks that are difficult adapt. To overcome these limitations, we propose a lightweight ensemble method, enhanced by pure correction, called Exceptionally Straightforward Ensemble. This approach...

Unsupervised learning with generative adversarial networks (GANs) has proven hugely successful. Regular GANs hypothesize the discriminator as a classifier sigmoid cross entropy loss function. However, we found that this function may lead to vanishing gradients problem during process. To overcome such problem, propose in paper Least Squares Generative Adversarial Networks (LSGANs) which adopt least squares for discriminator. We show minimizing objective of LSGAN yields Pearson $\chi^2$...