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Olga Kurasova, Arnoldas Bud?ys and Viktor Medvedev
As artificial intelligence has evolved, deep learning models have become important in extracting and interpreting complex patterns from raw multidimensional data. These models produce multidimensional embeddings that, while containing a lot of informatio...
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Shengkun Gu and Dejiang Wang
Within the domain of architectural urban informatization, the automated precision recognition of two-dimensional paper schematics emerges as a pivotal technical challenge. Recognition methods traditionally employed frequently encounter limitations due to...
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Ru Ye, Hongyan Xing and Xing Zhou
Addressing the limitations of manually extracting features from small maritime target signals, this paper explores Markov transition fields and convolutional neural networks, proposing a detection method for small targets based on an improved Markov tran...
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Atefe Sedaghat, Homayoon Arbabkhah, Masood Jafari Kang and Maryam Hamidi
This research introduces an online system for monitoring maritime traffic, aimed at tracking vessels in water routes and predicting their subsequent locations in real time. The proposed framework utilizes an Extract, Transform, and Load (ETL) pipeline to...
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Dongsheng Li, Jinfeng Ma, Kaifeng Rao, Xiaoyan Wang, Ruonan Li, Yanzheng Yang and Hua Zheng
Accurate rainfall prediction remains a challenging problem because of the high volatility and complicated essence of atmospheric data. This study proposed a hybrid model (DSP) that combines the advantages of discrete wavelet transform (DWT), support vect...
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