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Olga Kurasova, Arnoldas Bud?ys and Viktor Medvedev
As artificial intelligence has evolved, deep learning models have become important in extracting and interpreting complex patterns from raw multidimensional data. These models produce multidimensional embeddings that, while containing a lot of informatio...
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Rujia Li, Yadong Li, Weibo Qin, Arzlan Abbas, Shuang Li, Rongbiao Ji, Yehui Wu, Yiting He and Jianping Yang
This research tackles the intricate challenges of detecting densely distributed maize leaf diseases and the constraints inherent in YOLO-based detection algorithms. It introduces the GhostNet_Triplet_YOLOv8s algorithm, enhancing YOLO v8s by integrating t...
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Gergely Márk Csányi, Renátó Vági, Andrea Megyeri, Anna Fülöp , Dániel Nagy, János Pál Vadász and István Üveges
Few-shot learning is a deep learning subfield that is the focus of research nowadays. This paper addresses the research question of whether a triplet-trained Siamese network, initially designed for multi-class classification, can effectively handle multi...
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Wen-Chang Cheng, Hung-Chou Hsiao, Yung-Fa Huang and Li-Hua Li
This research proposes a single network model architecture for mask face recognition using the FaceNet training method. Three pre-trained convolutional neural networks of different sizes are combined, namely InceptionResNetV2, InceptionV3, and MobileNetV...
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Reihan Alinia Lat, Sebelan Danishvar, Hamed Heravi and Morad Danishvar
In recent years, the topic of contactless biometric identification has gained considerable traction due to the COVID-19 pandemic. One of the most well-known identification technologies is iris recognition. Determining the classification threshold for lar...
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Wenzuo Qiao, Wenjuan Ren and Liangjin Zhao
With the development and popularization of unmanned aerial vehicles (UAVs) and surveillance cameras, vehicle re-identification (ReID) task plays an important role in the field of urban safety. The biggest challenge in the field of vehicle ReID is how to ...
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Zhongmiao Huang, Liejun Wang, Yongming Li, Anyu Du and Shaochen Jiang
Currently, deep learning is the mainstream method to solve the problem of person reidentification. With the rapid development of neural networks in recent years, a number of neural network frameworks have emerged for it, so it is becoming more important ...
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Li Jiang, Xianghuan Liu, Haixia Wang and Dongdong Zhao
Multimodal biometric recognition involves two critical issues: feature representation and multimodal fusion. Traditional feature representation requires complex image preprocessing and different feature-extraction methods for different modalities. Moreov...
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Kun-Yi Chen, Chi-Yu Chang, Zhi-Ren Tsai, Chun-Ting Lee, Zon-Yin Shae
Pág. 199 - 212
To solve tea image classification problems, this study focuses on triplet loss convolutional neural network to classify six high-mountain oolong tea classes. In the experiment, instead of using traditional deep learning training approach for local featur...
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Xing Fan, Wei Jiang, Hao Luo, Weijie Mao and Hongyan Yu
Traditional Person Re-identification (ReID) methods mainly focus on cross-camera scenarios, while identifying a person in the same video/camera from adjacent subsequent frames is also an important question, for example, in human tracking and pose trackin...
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