A Feature Fusion Method with Guided Training for Classification Tasks

Zhang, Taohong; Fan, Suli; Hu, Junnan; Guo, Xuxu; Li, Qianqian; Zhang, Ying; Wulamu, Aziguli

doi:10.1155/2021/6647220

Cited by 7 publications

(4 citation statements)

References 46 publications

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“…The fine-tuning process involved freezing the network parameters of several preceding convolution layers and creating a new fully connected layer to be retrained. Feature fusion is an algorithm used to merge independent features into a unique feature to enable easy processing [ 33 ]. The ResNet50-based dual-CNN framework is specifically introduced and depicted in Figure 3 .…”

Section: Methodsmentioning

confidence: 99%

Identification of Soybean Mutant Lines Based on Dual-Branch CNN Model Fusion Framework Utilizing Images from Different Organs

Lin

Deng

et al. 2023

Plants

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The accurate identification and classification of soybean mutant lines is essential for developing new plant varieties through mutation breeding. However, most existing studies have focused on the classification of soybean varieties. Distinguishing mutant lines solely by their seeds can be challenging due to their high genetic similarities. Therefore, in this paper, we designed a dual-branch convolutional neural network (CNN) composed of two identical single CNNs to fuse the image features of pods and seeds together to solve the soybean mutant line classification problem. Four single CNNs (AlexNet, GoogLeNet, ResNet18, and ResNet50) were used to extract features, and the output features were fused and input into the classifier for classification. The results demonstrate that dual-branch CNNs outperform single CNNs, with the dual-ResNet50 fusion framework achieving a 90.22 ± 0.19% classification rate. We also identified the most similar mutant lines and genetic relationships between certain soybean lines using a clustering tree and t-distributed stochastic neighbor embedding algorithm. Our study represents one of the primary efforts to combine various organs for the identification of soybean mutant lines. The findings of this investigation provide a new path to select potential lines for soybean mutation breeding and signify a meaningful advancement in the propagation of soybean mutant line recognition technology.

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Section: Methodsmentioning

confidence: 99%

Identification of Soybean Mutant Lines Based on Dual-Branch CNN Model Fusion Framework Utilizing Images from Different Organs

Lin

Deng

et al. 2023

Plants

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“…Feature fusion is a data integration technique used to aggregate multiple feature sets extracted from multiple input data to generate a single feature set [19]. In image processing problems, it refers to the fusion of feature vectors of training images extracted from shared weight network layer and feature vectors composed of other numerical data [20]. It helps to learn image features fully for the description of their rich internal information [21].…”

Section: Feature Fusionmentioning

confidence: 99%

Applying Multimodal Data Fusion based on Deep Learning Methods for the Diagnoses of Neglected Tropical Diseases: A Systematic Review

Minyilu,

Abebe,

Meshesha

2024

Preprint

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Neglected tropical diseases (NTDs) are the most prevalent diseases worldwide affecting one-tenth of the world population. Although there are multiple approaches to diagnosing these diseases, using skin manifestations and lesions caused as a result of these diseases along with other medical records is the preferred method. This fact triggers the need to explore and implement a deep learning-based diagnostic model using multimodal data fusion (MMDF) techniques to enhance the diagnostic process. This paper, thus, endeavored to present a thorough systematic review of studies regarding the implementation of MMDF techniques for the diagnoses of skin-related NTDs. To achieve its objective, the study used the PRISMA method based on predefined questions and collected 427 articles from seven major and reputed sources and critically appraised each article. Since no previous studies were found regarding the implementation of MMDF for the diagnoses of skin related NTDs, similar studies using MMDF for the diagnoses of other skin diseases, such as skin cancer, were collected and analyzed in this review to extract information about the implementation of these methods. In doing so, various studies are analyzed using six different parameters including research approaches, disease selected for diagnosis, dataset, algorithms, performance achievements and future directions. Accordingly, although all the studies used diverse research methods and datasets based on their problem, deep learning-based convolutional neural networks (CNN) algorithms are found to be the most frequently used and best performing models in all studies reviewed.

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“…The development of basic work for children is related to age, and the development process is continuous and uninterrupted. The development of children's basic movements is a prerequisite for their normal life and learning [28,29].…”

Section: Children's Sportsmentioning

confidence: 99%

The Auxiliary Function of Intelligent Mobile Robot in the Standard Training of Children’s Sports Movement

Liu

Guo

2022

Wireless Communications and Mobile Computing

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Mobile robots belong to mechanical devices. Mobile robots are commanded by humans and restricted by the principles established by artificial intelligence technology, mainly to assist humans in dangerous tasks. Intelligent mobile robot is a system that integrates perception, analysis, and decision-making, and it integrates a number of high-end technologies. It is currently the most active field of technological development. Infant sport is essentially a process of cultivating and caring for the physical fitness of children. This article aims to explore the auxiliary role of intelligent mobile robots in the standard training of children’s sports movements. The physique of the early childhood stage is closely related to the entire life stage. Once there is a deviation in the early childhood training stage, there will be very serious consequences. Therefore, the mobile intelligent robot is combined with children’s physical training, and it is expected that it will give correct guidance to improve children’s physical fitness. This article briefly designs the mobile robot, uses two independent wheels and a robotic arm with degrees of freedom, and analyzes the forward and inverse kinematics of the chassis and the robotic arm, which provides a theoretical basis for the design of the control algorithm. This article will focus on the training of children’s sports, explore the current deficiencies in children’s sports, and analyze the reasons and the role that intelligent mobile robots can provide in sports training. The experimental results in this paper show that the balance ability of children standing on one foot with eyes open is mainly distributed in the second, third, and fourth levels. Among them, the second level has the largest number of people, accounting for 52%, the third level accounts for 27%, the fourth level accounts for 22%, and the other levels are less distributed. When the intelligent mobile robot assists children’s movement, the child’s balance ability is generally distributed in the fourth and fifth levels. Among them, the fourth level has the largest number of people, accounting for 52%, followed by the fifth level, accounting for 26%, and the third level accounting for 14%. This shows that the intelligent mobile robot is effective in guiding the movement of young children.

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A Feature Fusion Method with Guided Training for Classification Tasks

Cited by 7 publications

References 46 publications

Identification of Soybean Mutant Lines Based on Dual-Branch CNN Model Fusion Framework Utilizing Images from Different Organs

Identification of Soybean Mutant Lines Based on Dual-Branch CNN Model Fusion Framework Utilizing Images from Different Organs

Applying Multimodal Data Fusion based on Deep Learning Methods for the Diagnoses of Neglected Tropical Diseases: A Systematic Review

The Auxiliary Function of Intelligent Mobile Robot in the Standard Training of Children’s Sports Movement

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