15 papers · ranked by Valyu relevance
Cong Xu, Xuqi Wang, Shanwen Zhang
Accurate and rapid identification of apple leaf diseases is the basis for preventing and treating apple diseases. However, it is challenging to identify apple leaf diseases due to their various symptoms, different colors, irregular shapes, uneven sizes, and complex backgrounds. To reduce computational cost and improve…
Seyha Chim, Jin-Gu Lee, Ho-Hyun Park
Facial landmark detection has gained enormous interest for face-related applications due to its success in facial analysis tasks such as facial recognition, cartoon generation, face tracking and facial expression analysis. Many studies have been proposed and implemented to deal with the challenging problems of…
Tao Wang, Zenghui Ding, Xianjun Yang, Yanyan Chen + 4 more
'Xiaoming Kong' 'Yining Sun' 'Ivan Miguel Pires'] Mild cognitive impairment (MCI) is a precursor to neurodegenerative diseases such as Alzheimer’s disease, and an early diagnosis and intervention can delay its progression. However, the brain MRI images of MCI patients have small changes and blurry shapes. At the same…
Khaled R. Ahmed, Petros Daras
Roads make a huge contribution to the economy and act as a platform for transportation. Potholes in roads are one of the major concerns in transportation infrastructure. A lot of research has proposed using computer vision techniques to automate pothole detection that include a wide range of image processing and object…
Wei Wang, Yiyang Hu, Ting Zou, Hongmei Liu + 2 more
Because deep neural networks (DNNs) are both memory-intensive and computation-intensive, they are difficult to apply to embedded systems with limited hardware resources. Therefore, DNN models need to be compressed and accelerated. By applying depthwise separable convolutions, MobileNet can decrease the number of…
Xiajiong Shen, Kunying Meng, Lei Zhang, Xianyu Zuo
The neural network method can obtain a higher precision of radar echo extrapolation than the traditional method. However, its application in radar echo extrapolation is still in the initial stage of exploration, and there is still much room for improvement in the extrapolation accuracy. To improve the utilization of…
Pengyu Fu, Liang Chu, Jihao Li, Zhiqi Guo + 3 more
'Zhuoran Hou' 'Chris Rizos'] A battery’s charging data include the timing information with respect to the charge. However, the existing State of Health (SOH) prediction methods rarely consider this information. This paper proposes a dilated convolution-based SOH prediction model to verify the influence of charging…
Shanqin Wang, Miao Zhang, Mengjun Miao
Aiming at the problems of traditional image super-resolution reconstruction algorithms in the image reconstruction process, such as small receptive field, insufficient multi-scale feature extraction, and easy loss of image feature information, a super-resolution reconstruction algorithm of multi-scale dilated…
Zhen Wang, Buhong Wang, Jianxin Guo, Shanwen Zhang
Underwater sonar objective detection plays an important role in the field of ocean exploration. In order to solve the problem of sonar objective detection under the complex environment, a sonar objective detection method is proposed based on dilated separable densely connected convolutional neural networks (DS-CNNs)…
Zhiqiang Zhao, Peihong Ma, Meng Jia, Xiaofan Wang + 2 more
'Marcin Woźniak'] Crowd counting is an important task that serves as a preprocessing step in many applications. Despite obvious improvement reported by various convolutional-neural-network-based approaches, they only focus on the role of deep feature maps while neglecting the importance of shallow features for crowd…
Fengdan Hu, Haigen Hu, Hui Xu, Jinshan Xu + 2 more
Owing to the variable shapes, large size difference, uneven grayscale, and dense distribution among biological cells in an image, it is very difficult to accurately detect and segment cells. Especially, it is a serious challenge for some microscope imaging devices with limited resources owing to a large number of…
Sangun Park, Dong Eui Chang, Stefanos Kollias
Robot vision is an essential research field that enables machines to perform various tasks by classifying/detecting/segmenting objects as humans do. The classification accuracy of machine learning algorithms already exceeds that of a well-trained human, and the results are rather saturated. Hence, in recent years, many…
Chenming Li, Zelin Qiu, Xueying Cao, Zhonghao Chen + 3 more
'Zaijun Hua' 'Doo Seok Jeong'] The convolutional neural network (CNN) has been proven to have better performance in hyperspectral image (HSI) classification than traditional methods. Traditional CNN on hyperspectral image classification is used to pay more attention to spectral features and ignore spatial information.…
Jiacai Liao, Libo Cao, Wei Li, Xiaole Luo + 1 more
Linear feature extraction is crucial for special objects in semantic segmentation networks, such as slot marking and lanes. The objects with linear characteristics have global contextual information dependency. It is very difficult to capture the complete information of these objects in semantic segmentation tasks. To…
Ji Wang, Peiquan Xu, Leijun Li, Feng Zhang + 1 more
During steel production, various defects often appear on the surface of the steel, such as cracks, pores, scars, and inclusions. These defects may seriously decrease steel quality or performance, so how to timely and accurately detect defects has great technical significance. This paper proposes a lightweight model…