Contour wavelet diffusion – a fast and high-quality facial expression generation model by Chenwei Xu, Yuntao Zou

“…Latent space diffusion models have shown promise in speeding up training by leveraging feature space parameters, but they require additional network structures. …”
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A Hybrid Approach of DenseNet121 with Attention and Bi-LSTM for Yoga Pose Estimation by Aarthy K., Alice Nithya

“…This model enhances accuracy by incorporating self-attention mechanisms, allowing the system to focus on significant features within the data. Performance optimization is achieved through the Enhanced Chicken Swarm Optimization (ECSO) method, which fine-tunes the parameters of the system to ensure optimal results. …”
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Enhancing State of Health Prediction Accuracy in Lithium-Ion Batteries through a Simplified Health Indicator Method by Dongxu Han, Nan Zhou, Zeyu Chen

“…This paper conducts an in-depth analysis of the incremental capacity (IC) curve and proposes a feature parameter based on the area under the IC curve. …”
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Three-Dimensional Magnetotelluric Forward Modeling Using Multi-Task Deep Learning with Branch Point Selection by Fei Deng, Hongyu Shi, Peifan Jiang, Xuben Wang

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Forced Convection Heat Transfer in V-Pattern Folded Core Sandwich Structures by Sifeng Li, Zhijin Wang, Chen Zhou

“…Based on the periodic feature of folded core, a methodology to simulate the fully developed flow and heat transfer state with a few unit cells is developed. …”
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DeLA: An extremely faster network with decoupled local aggregation for large scale point cloud learning by Weikang Yang, Xinghao Lu, Binjie Chen, Chenlu Lin, Xueye Bao, Weiquan Liu, Yu Zang, Junyu Xu, Cheng Wang

“…Unlike simple pooling, neighborhood aggregation incorporates spatial relationships between points into the feature aggregation process, requiring repeated relationship learning and resulting in substantial computational redundancy. …”
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Predicting the spatio-temporal reproductive potential of Aedes aegypti by Mr Tarek Alrefae

“…We use approximate Bayesian computation (ABC) and aegypti abundance data to fit two unknown scaling parameters of Index Q and propose an approximate global solution for making projections in cases where local data is unavailable. …”
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Investigation on Pore-Fracture of Coal and Its Influence Mechanism on Tensile Failure Behavior of Coals with Bursting Proneness by Yutao Li, Qingwei Guo, Xunchen Liu, Yaodong Jiang, Bo Zhang, Hao Wang

“…The feature of acoustic emission parameters indicates that the deformation and failure process of a sample under loading could be divided into four stages: compaction stage, elastic deformation stage, displacement plastic growth stage, and post peak failure stage, which is the result of comprehensive action of many factors. …”
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YOLO-LSM: A Lightweight UAV Target Detection Algorithm Based on Shallow and Multiscale Information Learning by Chenxing Wu, Changlong Cai, Feng Xiao, Jiahao Wang, Yulin Guo, Longhui Ma

“…To address challenges such as large-scale variations, high density of small targets, and the large number of parameters in deep learning-based target detection models, which limit their deployment on UAV platforms with fixed performance and limited computational resources, a lightweight UAV target detection algorithm, YOLO-LSM, is proposed. …”
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Efficient automated detection of power quality disturbances using nonsubsampled contourlet transform & PCA-SVM by Pampa Sinha, Kaushik Paul, Asit Mohanty, IM Elzein, Chandra Sekhar Mishra, Mohamed Metwally Mahmoud, Daniel Eutyche Mbadjoun Wapet, Abdulrahman Al Ayidh, Ahmed Althobaiti, Hany S Hussein, Thamer AH Alghamdi, Ahmed M Ewais

“…These optimized features are used for training a multi-class support vector machine, with its parameters further optimized for enhanced classification accuracy. …”
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Research on SeaTreasure Target Detection Technology Based on Improved YOLOv7-Tiny by Xiang Shi, Yunli Zhao, Jinrong Guo, Yan Liu, Yongqi Zhang

“…First, based on the YOLOv7-Tiny network, the MAFPN neck structure is used to replace the ELAN structure to achieve the multi-scale capture of semantic information of underwater sea treasures, and to enhance the UPA-YOLO model to accurately locate the targets of underwater sea treasures; second, the P2ELAN module is constructed and added to the backbone network, which makes use of the redundancy information in the feature map and dynamically adjusts the convolution kernel to adapt to data The P2ELAN module is added to the backbone network, using the redundant information in the feature map, dynamically adjusting the convolutional kernel to adapt to the lack of data, reducing the number of parameters in the model, and introducing the MSCA attention mechanism to inhibit the complex and changeable background features underwater, to improve the semantic feature extraction ability of the UPA-YOLO model for underwater targets, adding the MPDiou loss function to the improved algorithm model and completing the data validation of the detection model; finally, based on the TensorRT acceleration framework, the optimisation of the target detection Finally, based on the TensorRT acceleration framework, the target detection model is optimised, and the Jetson Nano edge device is used to complete the localisation deployment and realise the real-time target detection task of underwater sea treasures. …”
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DSNET: A Lightweight Segmentation Model for Segmentation of Skin Cancer Lesion Regions by Yucong Chen, Guang Yang, Xiaohua Dong, Junying Zeng, Chuanbo Qin

“…This model achieves optimal segmentation performance while maintaining low model parameters and computational complexity. To reduce the model size and guarantee model segmentation performance, we proposed a detail-enhanced separable difference convolution as a base module in the model. …”
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E-MobileViT: a lightweight model for traffic sign recognition by Shiqi Song, Xinfeng Ye, Sathiamoorthy Manoharan

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Lightweight coal mine conveyor belt foreign object detection based on improved Yolov8n by Jierui Ling, Zhibo Fu, Xinpeng Yuan

“…Abstract To resolve the drawbacks of slow speed, excessive parameters, and high computational demands associated with deep learning-based conveyor belt foreign object detection methods, a lightweight algorithm for detecting foreign objects on conveyors based on an improved Yolov8n model is proposed. …”
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Pedestrian Detection in Fisheye Images Based on Improved YOLOv8 Algorithm by ZHU Yumin, SUN Guangling, MIAO Fei

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Keypoint Detection and 3D Localization Method for Ridge-Cultivated Strawberry Harvesting Robots by Shuo Dai, Tao Bai, Yunjie Zhao

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Efficient microaneurysm segmentation in retinal images via a lightweight Attention U-Net for early DR diagnosis by Muhammad Zeeshan Tahir, Xingzheng Lyu, Muhammad Nasir, Wengan He, Abeer Aljohani, Sanyuan Zhang

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The digital interactive design of mirror painting under transformer based intelligent rendering methods by Chenye Zhang

“…Second, Swin Transformer for global feature modeling is introduced to reduce complexity through sliding window attention mechanisms. …”
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Lightweight Multi-Head MambaOut with CosTaylorFormer for Hyperspectral Image Classification by Yi Liu, Yanjun Zhang, Jianhong Zhang

“…While transformers have been widely adopted for hyperspectral image classification due to their global feature extraction capabilities, their quadratic computational complexity limits their applicability for resource-constrained devices. …”
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SHAP Informed Neural Network by Jarrod Graham, Victor S. Sheng

“…The SHAP-informed adjustments integrate feature importance metrics derived from cooperative game theory, either scaling the global learning rate or directly modifying gradients of first-layer parameters. …”
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