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Youngki Park and Youhyun Shin
In this paper, we introduce an efficient approach to multi-label image classification that is particularly suited for scenarios requiring rapid adaptation to new classes with minimal training data. Unlike conventional methods that rely solely on neural n...
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Changan Wei, Qiqi Li, Ji Xu, Jingli Yang and Shouda Jiang
Deep learning is widely used in vision tasks, but feature extraction of IR small targets is difficult due to the inconspicuous contours and lack of color information. This paper proposes a new convolutional neural network?based (CNN-based) method for IR ...
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Joseph Pedersen, Rafael Muñoz-Gómez, Jiangnan Huang, Haozhe Sun, Wei-Wei Tu and Isabelle Guyon
We address the problem of defending predictive models, such as machine learning classifiers (Defender models), against membership inference attacks, in both the black-box and white-box setting, when the trainer and the trained model are publicly released...
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Jaekyung Kim, Jungwoo Huh, Ingu Park, Junhyeong Bak, Donggeon Kim and Sanghoon Lee
Deep learning-based object detection is one of the most popular research topics. However, in cases where large-scale datasets are unavailable, the training of detection models remains challenging due to the data-driven characteristics of deep learning. S...
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Rasheed Gbenga Jimoh, Olayinka Olufunmilayo Olusanya, Joseph Bamidele Awotunde, Agbotiname Lucky Imoize and Cheng-Chi Lee
In the field of software development, the efficient prioritizing of software risks was essential and play significant roles. However, finding a viable solution to this issue is a difficult challenge. The software developers have to adhere strictly to ris...
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Martin Jänicke, Bernhard Sick and Sven Tomforde
Personal wearables such as smartphones or smartwatches are increasingly utilized in everyday life. Frequently, activity recognition is performed on these devices to estimate the current user status and trigger automated actions according to the user?s ne...
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Mohammad Bagher Dowlatshahi, Vali Derhami and Hossein Nezamabadi-pour
Micro-Ribonucleic Acids (miRNAs) are small non-coding Ribonucleic Acid (RNA) molecules that play an important role in the cancer growth. There are a lot of miRNAs in the human body and not all of them are responsible for cancer growth. Therefore, there i...
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Michael O?Byrne, Vikram Pakrashi, Franck Schoefs and Bidisha Ghosh
Recent breakthroughs in the computer vision community have led to the emergence of efficient deep learning techniques for end-to-end segmentation of natural scenes. Underwater imaging stands to gain from these advances, however, deep learning methods req...
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