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Ryota Higashimoto, Soh Yoshida and Mitsuji Muneyasu
This paper addresses the performance degradation of deep neural networks caused by learning with noisy labels. Recent research on this topic has exploited the memorization effect: networks fit data with clean labels during the early stages of learning an...
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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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MohammadHossein Reshadi, Wen Li, Wenjie Xu, Precious Omashor, Albert Dinh, Scott Dick, Yuntong She and Michael Lipsett
Anomaly detection in data streams (and particularly time series) is today a vitally important task. Machine learning algorithms are a common design for achieving this goal. In particular, deep learning has, in the last decade, proven to be substantially ...
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Yang Zhang, Yuan Feng, Shiqi Wang, Zhicheng Tang, Zhenduo Zhai, Reid Viegut, Lisa Webb, Andrew Raedeke and Yi Shang
Waterfowl populations monitoring is essential for wetland conservation. Lately, deep learning techniques have shown promising advancements in detecting waterfowl in aerial images. In this paper, we present performance evaluation of several popular superv...
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Rui Zhang, Mingwei Yao, Zijie Qiu, Lizhuo Zhang, Wei Li and Yue Shen
Wheat breeding heavily relies on the observation of various traits during the wheat growth process. Among all traits, wheat head density stands out as a particularly crucial characteristic. Despite the realization of high-throughput phenotypic data colle...
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Yuejun Guo, Orhan Ermis, Qiang Tang, Hoang Trang and Alexandre De Oliveira
Signalling protocols are responsible for fundamental tasks such as initiating and terminating communication and identifying the state of the communication in telecommunication core networks. Signalling System No. 7 (SS7), Diameter, and GPRS Tunneling Pro...
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Hyunmin Gwak, Yongho Jeong, Chanyeong Kim, Yonghak Lee, Seongmin Yang and Sunghwan Kim
The key to semi-supervised semantic segmentation is to assign the appropriate pseudo-label to the pixels of unlabeled images. Recently, various approaches to consistency-based training and the filtering of reliable pseudo-labels have shown remarkable res...
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Shangchen Ma and Chunlin Song
Drivable road segmentation aims to sense the surrounding environment to keep vehicles within safe road boundaries, which is fundamental in Advance Driver-Assistance Systems (ADASs). Existing deep learning-based supervised methods are able to achieve good...
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Jialin Zhang, Mairidan Wushouer, Gulanbaier Tuerhong and Hanfang Wang
Emotional speech synthesis is an important branch of human?computer interaction technology that aims to generate emotionally expressive and comprehensible speech based on the input text. With the rapid development of speech synthesis technology based on ...
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Tingkai Hu, Zuqin Chen, Jike Ge, Zhaoxu Yang and Jichao Xu
Insufficiently labeled samples and low-generalization performance have become significant natural language processing problems, drawing significant concern for few-shot text classification (FSTC). Advances in prompt learning have significantly improved t...
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