|
|
|
|
|
Jian Ni, Rui Wang and Jing Tang
The detection of small objects is easily affected by background information, and a lack of context information makes detection difficult. Therefore, small object detection has become an extremely challenging task. Based on the above problems, we proposed...
ver más
|
|
|
|
|
|
|
|
|
|
|
Shengqin Bian, Xinyu He, Zhengguang Xu and Lixin Zhang
Noise filtering is a crucial task in digital image processing, performing the function of preprocessing. In this paper, we propose an algorithm that employs deep convolution and soft thresholding iterative algorithms to extract and learn the features of ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Hui Luo, Lianming Cai and Chenbiao Li
As the operational time of the railway increases, rail surfaces undergo irreversible defects. Once the defects occur, it is easy for them to develop rapidly, which seriously threatens the safe operation of trains. Therefore, the accurate and rapid detect...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jiapeng Cui and Feng Tan
Rice diseases are extremely harmful to rice growth, and achieving the identification and rapid classification of rice disease spots is an essential means to promote intelligent rice production. However, due to the large variety of rice diseases and the s...
ver más
|
|
|
|
|
|
|
|
|
|
|
Qian Zhang, Jie Ren, Hong Liang, Ying Yang and Lu Chen
Small object detection becomes a challenging problem in computer vision due to low resolution and less feature information. Making full use of high-resolution features is an important factor in improving small object detection. In this paper, to improve ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yuefeng Cen, Mingxing Luo, Gang Cen, Cheng Zhao and Zhigang Cheng
It is meaningful to analyze the market correlations for stock selection in the field of financial investment. Since it is difficult for existing deep clustering methods to mine the complex and nonlinear features contained in financial time series, in ord...
ver más
|
|
|
|
|
|
|
|
|
|
|
Wenjing Ran, Jiasheng Wang, Kun Yang, Ling Bai, Xun Rao, Zhe Zhao and Chunxiao Xu
To address the problem of low accuracy in line element recognition of raster maps due to text and background interference, we propose a raster map line element recognition method based on an improved U-Net network model, combining the semantic segmentati...
ver más
|
|
|
|
|
|
|
|
|
|
|
Gang Sun, Hancheng Yu, Xiangtao Jiang and Mingkui Feng
Edge detection is one of the fundamental computer vision tasks. Recent methods for edge detection based on a convolutional neural network (CNN) typically employ the weighted cross-entropy loss. Their predicted results being thick and needing post-process...
ver más
|
|
|
|
|
|
|
|
|
|
|
Alyaa Amer, Tryphon Lambrou and Xujiong Ye
The advanced development of deep learning methods has recently made significant improvements in medical image segmentation. Encoder?decoder networks, such as U-Net, have addressed some of the challenges in medical image segmentation with an outstanding p...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yong Qi, Mengzhe Qiu, Hefeifei Jiang and Feiyang Wang
The fingerprint is an important biological feature of the human body, which contains abundant biometric information. At present, the academic exploration of fingerprint gender characteristics is generally at the level of understanding, and the standardiz...
ver más
|
|
|
|
|
|