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Jie Ren, Changmiao Li, Yaohui An, Weichuan Zhang and Changming Sun
Few-shot fine-grained image classification (FSFGIC) methods refer to the classification of images (e.g., birds, flowers, and airplanes) belonging to different subclasses of the same species by a small number of labeled samples. Through feature representa...
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Shui Jiang, Yanning Ge, Xu Yang, Wencheng Yang and Hui Cui
Reinforcement learning (RL) is pivotal in empowering Unmanned Aerial Vehicles (UAVs) to navigate and make decisions efficiently and intelligently within complex and dynamic surroundings. Despite its significance, RL is hampered by inherent limitations su...
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Jinting Zhu, Julian Jang-Jaccard, Amardeep Singh, Paul A. Watters and Seyit Camtepe
Malware authors apply different techniques of control flow obfuscation, in order to create new malware variants to avoid detection. Existing Siamese neural network (SNN)-based malware detection methods fail to correctly classify different malware familie...
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Zheng Li, Xueyuan Huang, Liupeng Gong, Ke Yuan and Chun Liu
Next Point-of-Interest (POI) recommendation has shown great value for both users and providers in location-based services. Existing methods mainly rely on partial information in users? check-in sequences, and are brittle to users with few interactions. M...
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Shiwei Ruan, Hao Cang, Huixin Chen, Tianying Yan, Fei Tan, Yuan Zhang, Long Duan, Peng Xing, Li Guo, Pan Gao and Wei Xu
Early detection and diagnosis of crop anomalies is crucial for enhancing crop yield and quality. Recently, the combination of machine learning and deep learning with hyperspectral images has significantly improved the efficiency of crop detection. Howeve...
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Anastasios Kaltsounis, Evangelos Spiliotis and Vassilios Assimakopoulos
We present a machine learning approach for applying (multiple) temporal aggregation in time series forecasting settings. The method utilizes a classification model that can be used to either select the most appropriate temporal aggregation level for prod...
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Tianshu Zhang, Wenwen Dai, Zhiyu Chen, Sai Yang, Fan Liu and Hao Zheng
Due to their compelling performance and appealing simplicity, metric-based meta-learning approaches are gaining increasing attention for addressing the challenges of few-shot image classification. However, many similar methods employ intricate network ar...
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Xuyang Wang, Yajun Du, Danroujing Chen, Xianyong Li, Xiaoliang Chen, Yongquan Fan, Chunzhi Xie, Yanli Li and Jia Liu
Domain-generalized few-shot text classification (DG-FSTC) is a new setting for few-shot text classification (FSTC). In DG-FSTC, the model is meta-trained on a multi-domain dataset, and meta-tested on unseen datasets with different domains. However, previ...
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Shuang Guo, Yarong Du and Liang Liu
In order to achieve reliability, security, and scalability, the request flow in the Internet of Things (IoT) needs to pass through the service function chain (SFC), which is composed of series-ordered virtual network functions (VNFs), then reach the dest...
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Noa Mansbach and Amos Azaria
It is difficult to overestimate the importance of detecting human deception, specifically by using speech cues. Indeed, several works attempt to detect deception from speech. Unfortunately, most works use the same people and environments in training and ...
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