Zobrazeno 1 - 10
of 168
pro vyhledávání: '"Jiang Jianan"'
Although convolutional neural networks have made outstanding achievements in visible light target detection, there are still many challenges in infrared small object detection because of the low signal-to-noise ratio, incomplete object structure, and
Externí odkaz:
http://arxiv.org/abs/2408.07455
Autor:
Jiang, Jianan, Wu, Di, Deng, Hanhui, Long, Yidan, Tang, Wenyi, Li, Xiang, Liu, Can, Jin, Zhanpeng, Zhang, Wenlei, Qi, Tangquan
The process of fashion design usually involves sketching, refining, and coloring, with designers drawing inspiration from various images to fuel their creative endeavors. However, conventional image search methods often yield irrelevant results, impe
Externí odkaz:
http://arxiv.org/abs/2408.00855
ARNet: Self-Supervised FG-SBIR with Unified Sample Feature Alignment and Multi-Scale Token Recycling
Fine-Grained Sketch-Based Image Retrieval (FG-SBIR) aims to minimize the distance between sketches and corresponding images in the embedding space. However, scalability is hindered by the growing complexity of solutions, mainly due to the abstract na
Externí odkaz:
http://arxiv.org/abs/2406.11551
In the realm of fashion design, sketches serve as the canvas for expressing an artist's distinctive drawing style and creative vision, capturing intricate details like stroke variations and texture nuances. The advent of sketch-to-image cross-modal t
Externí odkaz:
http://arxiv.org/abs/2403.08651
Publikováno v:
In Aquaculture 15 February 2025 596 Part 1
Publikováno v:
In Neurocomputing 7 February 2025 617
Publikováno v:
In Marine Pollution Bulletin February 2025 211
Autor:
Long, Peihua a, 1, Ma, Qunfei a, 1, Wang, Zhe a, Wang, Guanqin a, Jiang, Jianan a, Gao, Lu a, b, ⁎
Publikováno v:
In Heliyon 15 September 2024 10(17)
Autor:
Li, Yahe, Jiang, Jianan, Zhang, Ruihong, Qie, Wandi, Shao, Jianzhong, Zhu, Wenrong, Xu, Nianjun
Publikováno v:
In Marine Environmental Research May 2024 197
Domain adaptation, as a task of reducing the annotation cost in a target domain by exploiting the existing labeled data in an auxiliary source domain, has received a lot of attention in the research community. However, the standard domain adaptation
Externí odkaz:
http://arxiv.org/abs/2012.01606