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Peranut Nimitsurachat and Peter Washington
Emotion recognition models using audio input data can enable the development of interactive systems with applications in mental healthcare, marketing, gaming, and social media analysis. While the field of affective computing using audio data is rich, a m...
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Tao Tang, Yuting Cui, Rui Feng and Deliang Xiang
With the development of deep learning in the field of computer vision, convolutional neural network models and attention mechanisms have been widely applied in SAR image target recognition. The improvement of convolutional neural network attention in exi...
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Youngkwang Kim, Woochan Kim, Jungwoo Yoon, Sangkug Chung and Daegeun Kim
This paper presents a practical contamination detection system for camera lenses using image analysis with deep learning. The proposed system can detect contamination in camera digital images through contamination learning utilizing deep learning, and it...
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Jiahui Zhao, Zhibin Li, Pan Liu, Mingye Zhang
Pág. 115 - 142
Demand prediction plays a critical role in traffic research. The key challenge of traffic demand prediction lies in modeling the complex spatial dependencies and temporal dynamics. However, there is no mature and widely accepted concept to support the so...
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Jun Li, Chenyang Zhang, Jianyi Zhang and Yanhua Shao
To address the challenge of balancing privacy protection with regulatory oversight in blockchain transactions, we propose a regulatable privacy protection scheme for blockchain transactions. Our scheme utilizes probabilistic public-key encryption to obsc...
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Min Ma, Shanrong Liu, Shufei Wang and Shengnan Shi
Automatic modulation classification (AMC) plays a crucial role in wireless communication by identifying the modulation scheme of received signals, bridging signal reception and demodulation. Its main challenge lies in performing accurate signal processin...
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Mohammad Alhumaid and Ayman G. Fayoumi
Paranasal sinus pathologies, particularly those affecting the maxillary sinuses, pose significant challenges in diagnosis and treatment due to the complex anatomical structures and diverse disease manifestations. The aim of this study is to investigate t...
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Julia Mayer, Martin Memmel, Johannes Ruf, Dhruv Patel, Lena Hoff and Sascha Henninger
Urban tree cadastres, crucial for climate adaptation and urban planning, face challenges in maintaining accuracy and completeness. A transdisciplinary approach in Kaiserslautern, Germany, complements existing incomplete tree data with additional precise ...
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Jiarui Xia and Yongshou Dai
Ground roll noise suppression is a crucial step in processing deep pre-stack seismic data. Recently, supervised deep learning methods have gained popularity in this field due to their ability to adaptively learn and extract powerful features. However, th...
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Bo Zhao, Qifan Zhang, Yangchun Liu, Yongzhi Cui and Baixue Zhou
In response to the need for precision and intelligence in the assessment of transplanting machine operation quality, this study addresses challenges such as low accuracy and efficiency associated with manual observation and random field sampling for the ...
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