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Xinwei Lyu, Xinjia Li, Yuexin Zhang and Wenlian Lu
The rapid expansion of e-commerce, particularly in the clothing sector, has led to a significant demand for an effective clothing industry. This study presents a novel two-stage image recognition method. Our approach distinctively combines human keypoint...
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Mingxin Zou, Yanqing Zhou, Xinhua Jiang, Julin Gao, Xiaofang Yu and Xuelei Ma
Field manual labor behavior recognition is an important task that applies deep learning algorithms to industrial equipment for capturing and analyzing people?s behavior during field labor. In this study, we propose a field manual labor behavior recogniti...
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Sonia Díaz-Santos, Óscar Cigala-Álvarez, Ester Gonzalez-Sosa, Pino Caballero-Gil and Cándido Caballero-Gil
This paper introduces a cutting-edge approach that combines facial recognition and drowsiness detection technologies with Internet of Things capabilities, including 5G/6G connectivity, aimed at bolstering vehicle security and driver safety. The delineate...
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Yuntao Shi, Hongfei Zhang, Wei Guo, Meng Zhou, Shuqin Li, Jie Li and Yu Ding
This research proposes a face detection algorithm named LighterFace, which is aimed at enhancing detection speed to meet the demands of real-time community applications. Two pre-trained convolutional neural networks are combined, namely Cross Stage Parti...
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AlsharifHasan Mohamad Aburbeian and Manuel Fernández-Veiga
Securing online financial transactions has become a critical concern in an era where financial services are becoming more and more digital. The transition to digital platforms for conducting daily transactions exposed customers to possible risks from cyb...
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Ping Dong, Kuo Li, Ming Wang, Feitao Li, Wei Guo and Haiping Si
In addition to the conventional situation of detecting a single disease on a single leaf in corn leaves, there is a complex phenomenon of multiple diseases overlapping on a single leaf (compound diseases). Current research on corn leaf disease detection ...
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Hailiang Gong, Xi Wang and Weidong Zhuang
This study focuses on real-time detection of maize crop rows using deep learning technology to meet the needs of autonomous navigation for weed removal during the maize seedling stage. Crop row recognition is affected by natural factors such as soil expo...
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Rong Wang, Xinyang Zhou, Yi Liu, Dongqi Liu, Yu Lu and Miao Su
To ensure the safety and durability of concrete structures, timely detection and classification of concrete cracks using a low-cost and high-efficiency method is necessary. In this study, a concrete surface crack damage detection method based on the ResN...
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Qiuyue Li, Hao Sheng, Mingxue Sheng and Honglin Wan
Efficient document recognition and sharing remain challenges in the healthcare, insurance, and finance sectors. One solution to this problem has been the use of deep learning techniques to automatically extract structured information from paper documents...
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Sepideh Molaei, Stefano Cirillo and Giandomenico Solimando
MicroRNAs (miRNAs) play a crucial role in cancer development, but not all miRNAs are equally significant in cancer detection. Traditional methods face challenges in effectively identifying cancer-associated miRNAs due to data complexity and volume. This ...
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