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Yefeng Sun, Liang Gong, Wei Zhang, Bishu Gao, Yanming Li and Chengliang Liu
Drivable area detection is crucial for the autonomous navigation of agricultural robots. However, semi-structured agricultural roads are generally not marked with lanes and their boundaries are ambiguous, which impedes the accurate segmentation of drivab...
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Qingtian Ke and Peng Zhang
Change detection based on bi-temporal remote sensing images has made significant progress in recent years, aiming to identify the changed and unchanged pixels between a registered pair of images. However, most learning-based change detection methods only...
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Yajing Xu, Haitao Yang, Si Li, Xinyi Wang and Mingfei Cheng
Visual relationship detection (VRD), a challenging task in the image understanding, suffers from vague connection between relationship patterns and visual appearance. This issue is caused by the high diversity of relationship-independent visual appearanc...
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Birgitta Dresp-Langley
Two universal functional principles of Grossberg?s Adaptive Resonance Theory decipher the brain code of all biological learning and adaptive intelligence. Low-level representations of multisensory stimuli in their immediate environmental context are form...
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Junda Li, Chunxu Zhang and Bo Yang
Current two-stage object detectors extract the local visual features of Regions of Interest (RoIs) for object recognition and bounding-box regression. However, only using local visual features will lose global contextual dependencies, which are helpful t...
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Krenar Ibrahimi
Pág. 261 - 278
This paper shows how and why a theoretical framework to (re)conceptualize seaports as institutional and operational clusters may be constructed. Using a thorough review and content analysis of the seaport literature, six interrelated contextual dimension...
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Ke Zhao, Lan Huang, Rui Song, Qiang Shen and Hao Xu
Short text classification is an important problem of natural language processing (NLP), and graph neural networks (GNNs) have been successfully used to solve different NLP problems. However, few studies employ GNN for short text classification, and most ...
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Graham Spinks and Marie-Francine Moens
This paper proposes a novel technique for representing templates and instances of concept classes. A template representation refers to the generic representation that captures the characteristics of an entire class. The proposed technique uses end-to-end...
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Abdullah Y. Muaad, Hanumanthappa Jayappa, Mugahed A. Al-antari and Sungyoung Lee
Arabic text classification is a process to simultaneously categorize the different contextual Arabic contents into a proper category. In this paper, a novel deep learning Arabic text computer-aided recognition (ArCAR) is proposed to represent and recogni...
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Guizhe Song, Degen Huang and Zhifeng Xiao
Multilingual characteristics, lack of annotated data, and imbalanced sample distribution are the three main challenges for toxic comment analysis in a multilingual setting. This paper proposes a multilingual toxic text classifier which adopts a novel fus...
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Wenjing Yang, Liejun Wang, Shuli Cheng, Yongming Li and Anyu Du
Recently, deep learning to hash has extensively been applied to image retrieval, due to its low storage cost and fast query speed. However, there is a defect of insufficiency and imbalance when existing hashing methods utilize the convolutional neural ne...
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Dan Ezequiel Kröhling, Omar Chiotti, Ernesto Martínez
Pág. 135 - 149
Automated negotiation between artificial agents is essential to deploy Cognitive Computing and Internet of Things. The behavior of a negotiation agent depends significantly on the influence of environmental conditions or contextual variables, since they ...
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Thomas Wiesner
Pág. 124 - 145
The actual, globally established, general digital procedures in basic architectural education,producing well-behaved, seemingly attractive up-to-date projects, spaces and first general-researchon all scale levels, apparently present a certain growing amo...
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Yubo Zheng, Yingying Luo, Hengyi Shao, Lin Zhang and Lei Li
Contrastive learning, as an unsupervised technique, has emerged as a prominent method in time series representation learning tasks, serving as a viable solution to the scarcity of annotated data. However, the application of data augmentation methods duri...
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Pingshan Liu, Qi Liang and Zhangjing Cai
Aiming at addressing the inability of traditional web technologies to effectively respond to Winter-Olympics-related user questions containing multiple intentions, this paper explores a multi-model fusion-based multi-intention recognition model BCNBLMATT...
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Xiaocong Wei, Hongfei Lin, Liang Yang and Yuhai Yu
Learners in a massive open online course often express feelings, exchange ideas and seek help by posting questions in discussion forums. Due to the very high learner-to-instructor ratios, it is unrealistic to expect instructors to adequately track the fo...
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Ruoyang Li, Shuping Xiong, Yinchao Che, Lei Shi, Xinming Ma and Lei Xi
Semantic segmentation algorithms leveraging deep convolutional neural networks often encounter challenges due to their extensive parameters, high computational complexity, and slow execution. To address these issues, we introduce a semantic segmentation ...
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Xiu Li, Aron Henriksson, Martin Duneld, Jalal Nouri and Yongchao Wu
Educational content recommendation is a cornerstone of AI-enhanced learning. In particular, to facilitate navigating the diverse learning resources available on learning platforms, methods are needed for automatically linking learning materials, e.g., in...
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Xiaohui Cui, Yu Yang, Dongmei Li, Xiaolong Qu, Lei Yao, Sisi Luo and Chao Song
Recently, researchers have extensively explored various methods for electronic medical record named entity recognition, including character-based, word-based, and hybrid methods. Nonetheless, these methods frequently disregard the semantic context of ent...
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Xinzhi Wang, Mengyue Li, Quanyi Liu, Yudong Chang and Hui Zhang
The accurate analysis of multi-scale flame development plays a crucial role in improving firefighting decisions and facilitating smart city establishment. However, flames? non-rigid nature and blurred edges present challenges in achieving accurate segmen...
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