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Bin Li, Huazhong Lu, Xinyu Wei, Shixuan Guan, Zhenyu Zhang, Xingxing Zhou and Yizhi Luo
Accurate litchi identification is of great significance for orchard yield estimations. Litchi in natural scenes have large differences in scale and are occluded by leaves, reducing the accuracy of litchi detection models. Adopting traditional horizontal ...
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Hui Zhou, Peng Chen, Yingqiu Li and Bo Wang
Ship detection in large-scene offshore synthetic aperture radar (SAR) images is crucial in civil and military fields, such as maritime management and wartime reconnaissance. However, the problems of low detection rates, high false alarm rates, and high m...
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Juan Chen, Zhencai Zhu, Haiying Hu, Lin Qiu, Zhenzhen Zheng and Lei Dong
The infrared detector is adopted to track and recognize targets, including missiles and airplanes. These targets are usually far from the detector. The pixel size is less than 9×9" role="presentation">9×99×9
9
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when the image has 256
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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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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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Yiming Mo, Lei Wang, Wenqing Hong, Congzhen Chu, Peigen Li and Haiting Xia
The intrusion of foreign objects on airport runways during aircraft takeoff and landing poses a significant safety threat to air transportation. Small-scale Foreign Object Debris (FOD) cannot be ruled out on time by traditional manual inspection, and the...
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Feng Guo, Hongbing Ma, Liangliang Li, Ming Lv and Zhenhong Jia
In the realm of maritime target detection, infrared imaging technology has become the predominant modality. Detecting infrared small ships on the sea surface is crucial for national defense and maritime security. However, the challenge of detecting infra...
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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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Nicholas Petzinna, Vladimir Nikora, Joe Onoufriou and Benjamin J. Williamson
With rising interest in marine renewable energy (MRE) associated with offshore wind, waves, and tidal flows, the effects of device placement on changes in animal behaviour require proper assessment to minimise environmental impacts and inform decision ma...
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Yuchao Wang, Jingdong Li, Zeming Chen and Chenglong Wang
In order to solve the problem of low accuracy of small target detection in traditional target detection algorithms, the YOLOX algorithm combined with Convolutional Block Attention Module (CBAM) is proposed. The algorithm first uses CBAM on the shallow fe...
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Liming Zhou, Chang Zheng, Haoxin Yan, Xianyu Zuo, Yang Liu, Baojun Qiao and Yong Yang
Recent years have seen rapid progress in target-detection missions, whereas small targets, dense target distribution, and shadow occlusion continue to hinder progress in the detection of small targets, such as cars, in remote sensing images. To address t...
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Yan Yan and Hongyan Xing
In order for the detection ability of floating small targets in sea clutter to be improved, on the basis of the complete ensemble empirical mode decomposition (CEEMD) algorithm, the high-frequency parts and low-frequency parts are determined by the energ...
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Huaiwen Wang, Jianguo Feng and Honghuan Yin
Images captured using unmanned aerial vehicles (UAVs) often exhibit dense target distribution and indistinct features, which leads to the issues of missed detection and false detection in target detection tasks. To address these problems, an improved met...
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Linhua Zhang, Ning Xiong, Wuyang Gao and Peng Wu
With the exponential growth of remote sensing images in recent years, there has been a significant increase in demand for micro-target detection. Recently, effective detection methods for small targets have emerged; however, for micro-targets (even fewer...
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Kun Wang, Defu Jiang, Lijun Yun and Xiaoyang Liu
Authors are encouraged to provide a concise description of the specific application or a potential application of the work. This section is not mandatory.
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Yaming Cao, ZHEN YANG, CHEN GAO
Pág. 21 - 32
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Shuai Liu and Jialan Tang
Small object detection in very-high-resolution (VHR) optical remote sensing images is a fundamental but challenaging problem due to the latent complexities. To tackle this problem, the MdrlEcf model is proposed by modifying deep reinforcement learning (D...
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Jiangkun Gong, Jun Yan, Huiping Hu, Deyong Kong and Deren Li
The detection of drones using radar presents challenges due to their small radar cross-section (RCS) values, slow velocities, and low altitudes. Traditional signal-to-noise ratio (SNR) detectors often fail to detect weak radar signals from small drones, ...
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Junchi Zhou, Wenwu Hu, Airu Zou, Shike Zhai, Tianyu Liu, Wenhan Yang and Ping Jiang
Considering the high requirements of current kiwifruit picking recognition systems for mobile devices, including the small number of available features for image targets and small-scale aggregation, an enhanced YOLOX-S target detection algorithm for kiwi...
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Lisang Liu, Chengyang Ke and He Lin
In foggy environments, outdoor insulator detection is always with low visibility and unclear targets. Meanwhile, the scale of haze simulation insulator datasets is insufficient. Aiming to solve these problems, this paper proposes a novel Dark-Center algo...
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