The Application of Deep Learning in Dance Movement Design by Xiang Ju

“…Refinement in feature extraction and using deep new models such as ResNet-152 for pose recognition have helped to capitalize on model overfitting and worse generalization problems. …”
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LGN-YOLO: A Leaf-Oriented Region-of-Interest Generation Method for Cotton Top Buds in Fields by Yufei Xie, Liping Chen

“…As small-sized targets, cotton top buds pose challenges for traditional full-image search methods, leading to high sparsity in the feature matrix and resulting in problems such as slow detection speeds and wasted computational resources. …”
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Benchmarking Quantum Machine Learning Kernel Training for Classification Tasks by Diego Alvarez-Estevez

“…In particular, it examines the performance of quantum kernel estimation and quantum kernel training (QKT) in connection with two quantum feature mappings, namely, ZZFeatureMap and CovariantFeatureMap. …”
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Monocular Object-Level SLAM Enhanced by Joint Semantic Segmentation and Depth Estimation by Ruicheng Gao, Yue Qi

“…Specifically, feature fusion facilitates the sharing of features between the two tasks, while semantic consistency aims to guarantee the semantic segmentation and depth consistency among various views. …”
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Going Underground: An Experimental Archaeological Investigation of an Early Medieval Irish Souterrain by Tom Meharg

“…The subterranean structure is based on one of over 3,500 examples of this feature identified in Ireland. The project allowed us to interact with the similar problems likely facing past societies in regards to design and engineering. …”
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Design and Analysis of a Novel Micromanipulation Robot Mechanism by Sun Jianhua, Gu Hai, Zhang Jie, Li Bin

“…Firstly,the mobility and motion feature of this 5-DOF mechanism is analyzed with the constraint screw method.Then the inverse and forward displacement problems of the proposed hybrid mechanism are solved according to the geometrical relationship,and the Jacobian matrix of the mechanism is obtained based on the forward and inverse solution,the decoupled feature of the proposed parallel mechanism is validated. …”
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Gear Fault Diagnosis based on Variational Mode Decomposition and ANFIS by Zheng Xiaoxia, Jia Wenhui, Zhou Guowang, Li Jia

“…In order to solve the fault recognition problems caused by a complex signal transfer path,severe noise pollution and the weak fault features,a method for gear based on variational mode decomposition（ VMD）and adaptive neuro-fuzzy inference system（ ANFIS） is proposed. …”
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Classification of landscape architecture design based on dual-channel attention improved FCN by Zhongyu Zhou

“…Landscape architecture design integrates natural and artificial landscapes, and needs to accurately categorize diverse landscape elements. To solve the problems of low efficiency and high subjectivity of traditional design, the study proposes an improved fully convolutional network model that combines the U-Net structure, multi-scale hopping connection network, and dual-channel attention mechanism to enhance the ability of detail capture and feature fusion. …”
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Computerized diagnosis of prostate cancer based on whole slide histology images and deep learning methods by V. A. Kovalev, D. M. Voynov, V. D. Malyshau, E. D. Lapo

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Sovereign Authority and the Limits of Constitutional Democracy by Trevor Allen Purvis

“…The victory of Justin Trudeau’s Liberals in the Canadian federal election of 2015 brought with it hopes for meaningful change in the relationship between indigenous peoples and settler-Canadian society, with “reconciliation” a prominent feature of the new government’s discourse. But long on symbolism, the new government’s efforts have been markedly short on substance, and all good intentions seem unlikely to dislodge the more stubborn problems underpinning the relationship between indigenous peoples and the settler state that claims sovereignty over their lives. …”
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A Hybrid Method for Traffic Incident Duration Prediction Using BOA-Optimized Random Forest Combined with Neighborhood Components Analysis by Qiang Shang, Derong Tan, Song Gao, Linlin Feng

“…Firstly, the NCA is applied to select feature variables for traffic incident duration. Then, RF model is trained based on the training set constructed using feature variables, and the BOA is employed to optimize the RF parameters. …”
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Intrusion Detection-Data Security Protection Scheme Based on Particle Swarm-BP Network Algorithm in Cloud Computing Environment by Zhun Wang, Xue Chen

“…Then, by introducing the decision tree algorithm, the overfitting is reduced and the data processing speed of the model is improved, and on this basis, the feature selection is carried out through the “gain rate” optimization method, which reduces the redundant information of the feature vector. …”
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Application of artificial neural networks to the recognition of musical sounds by B. KOSTEK, R. KRÓLIKOWSKI

“…Results show that NNs (neural networks) are able to generalize information included in feature vectors. Therefore, when presenting data to NN inputs, there is no problem with variation of parameters within data, and consequently with data clustering, because a NN has the ability to generalize information during the learning phase. …”
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Multi-Step Dynamic Ensemble Selection to Estimate Software Effort by Akshay Jadhav, Shishir Kumar Shandilya, Ivan Izonin, Roman Muzyka

“…The performance of the proposed model is evaluated based on the K nearest neighbor oracle (KNORA) canonical approach to DES and in order to reduce the complexity, filter feature selection techniques are applied to extract the relevant feature set. …”
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MixRformer: Dual-Branch Network for Underwater Image Enhancement in Wavelet Domain by Jie Li, Lei Zhao, Heng Li, Xiaojun Xue, Hui Liu

“…This paper proposes an underwater image enhancement model MixRformer that combines the wavelet transform and a hybrid architecture. To address the problems of insufficient global modeling in existing CNN models, weak local feature extraction of Transformer and high computational complexity, multi-resolution feature decomposition is performed through a discrete wavelet transform (IWT/DWT) in which low-frequency components retain structure and texture, and high-frequency components capture detail features. …”
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Coal and gas outburst prediction based on data augmentation and neuroevolution. by Wenbing Shi, Ji Huang, Gaoming Yang, Shuzhi Su, Shexiang Jiang

“…It solves the problems of imbalanced data samples and insufficient diversity. …”
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Lightweight Transformer traffic scene semantic segmentation algorithm integrating multi-scale depth convolution by Gang XIE, Quanyi WANG, Xinlin XIE, Jian’an WANG

“…Aiming at the problems of discontinuous segmentation of thin strip objects that were easy to blend into the surrounding background and a large number of model parameters in the semantic segmentation algorithm of traffic scenes, a lightweight Transformer traffic scene semantic segmentation algorithm integrating multi-scale depth convolution was proposed.First, a multi-scale strip feature extraction module (MSEM) was constructed based on deep convolution to enhance the representation ability of thin strip target features at different scales.Secondly, a spatial detail auxiliary module (SDAM) was designed using the convolutional inductive bias feature in the shallow network to compensate for the loss of deep spatial detail information to optimize object edge segmentation.Finally, an asymmetric encoding-decoding network based on the Transformer-CNN framework (TC-AEDNet) was proposed.The encoder combined Transformer and CNN to alleviate the loss of detail information and reduce the amount of model parameters; while the decoder adopted a lightweight multi-level feature fusion design to further model the global context.The proposed algorithm achieves the mean intersection over union (mIoU) of 78.63% and 81.06% respectively on the Cityscapes and CamVid traffic scene public datasets.It can achieve a trade-off between segmentation accuracy and model size in traffic scene semantic segmentation and has a good application prospect.…”
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Intelligent recognition algorithm of connection relation of substation secondary wiring drawing based on D-LLE algorithm by Hongzhi Liu, Bojie Yang, Fang Kang, Qian Li, Hongyang Zhang

“…D-LLE algorithm (Denoised Locally Linear Embedding) is used to effectively extract the connection features in the drawings, which improves the feature expression ability and recognition accuracy. …”
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A Non-invasive Load Recognition Approach Incorporating SENet Attention Mechanism and GA-CNN by Xin SHEN, Gang WANG, Yitao ZHAO, Zhao LUO, Zhao LI, Xiaohua YANG

“…With the popularization of smart meters and the gradual improvement of grid informatization and digitization, non-intrusive load monitoring (NILM) on the demand side of residential customers' energy usage is becoming one of the key technologies for power supply companies to boost energy efficiency. Regarding the problems of the current non-intrusive load recognition algorithms, such as feature redundancy, high computational overhead, and low recognition performance, the paper proposes a non-intrusive load recognition method integrating SENet attention mechanism and GA-CNN. …”
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Elevator Running Fault Monitoring Method Based on Vibration Signal by Mingxing Jia, Xiongfei Gao, Hongru Li, Hali Pang

“…According to the one-dimensional characteristics of the vibration signal, this paper proposes an elevator operation fault monitoring method based on one-dimensional convolutional neural network (1-DCNN). It can solve the problems of traditional elevator fault monitoring methods that require complex feature extraction processes and a large amount of diagnostic experience. …”
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