Real-Time Optical Spectrum Fourier Transform With Time–Bandwidth Product Compression by Hao Sun, Xinyi Zhu, Wei Li, Ninghua Zhu, Ming Li

“…In addition, since the dispersive delay line could be programmable with high resolution, this technique is adaptable for different optical spectra and realizable for a reconfigurable TBP compression ratio. …”
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Small Ship Detection Based on Improved Neural Network Algorithm and SAR Images by Jiaqi Li, Hongyuan Huo, Li Guo, De Zhang, Wei Feng, Yi Lian, Long He

“…Secondly, multiple Depthwise Separable Convolution layers are added to the SPPF (Spatial Pyramid Pooling-Fast) structure. …”
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Spectrum sensing based on adversarial transfer learning by Jiawu Miao, Yuebo Li, Xiaojun Jing, Fangpei Zhang, Junsheng Mu

“…After that, the pre‐trained CNN model is distributed to local nodes with different SNRs and the pre‐trained CNN model is fine‐tuned. …”
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Linguistic-visual based multimodal Yi character recognition by Haipeng Sun, Xueyan Ding, Zimeng Li, Jian Sun, Hua Yu, Jianxin Zhang

“…Finally, a fusion strategy utilizing the cross-attention mechanism is employed to refine the relationships between feature regions and combine features from different modalities, thereby achieving high-precision character recognition. …”
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An Edge Recognition Method for Insulator State Based on Multi-dimension Feature Fusion by Dongmei HUANG, Yueqi WANG, Anduo HU, Jinzhong SUN, Shuai SHI, Yuan SUN, Lingfeng FANG

“…And a deep learning network integrating multi-dimension feature extraction is designed, which, by using the ResNet101 as the main feature extraction network, uses the Inception module to build the data pooling layer, and embeds the compression incentive module and convolution attention module to extract features from different dimensions. …”
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Soft-sediment Deformation Structures and Sand Body Architecture in the Chang 6 Oil Member of the Upper Triassic Yanchang Formation, Southwestern Ordos Basin, China by Qingshao Liang, Jingchun Tian, Feng Wang, Xiang Zhang

“…As a consequence, genetic models of the sand bodies formed by different sedimentation processes are established.…”
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Evaluation of a Deep Learning Model for Automatic Detection of Schizophrenia Using EEG Signals by Swetha Padmavathi Polisetty, Radhamani Ellapparaj, Karthikeyan M P

“…After data preprocessing to reduce noise and artifacts from EEGs, an 11-layer deep learning model consisting of convolution and LSTM layers with LeakyReLU activation function and different kernel sizes was implemented to automatically extract and classify features. …”
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Enhancing anemia detection through multimodal data fusion: a non-invasive approach using EHRs and conjunctiva images by Muhammad Ramzan, Muhammad Usman Saeed, Ghulam Ali

“…The important information from the concatenated features is selected with the help of a professional healthcare consultant. The different experiments are performed on textual and image datasets individually and after concatenating. …”
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Non-end-to-end adaptive graph learning for multi-scale temporal traffic flow prediction. by Kang Xu, Bin Pan, MingXin Zhang, Xuan Zhang, XiaoYu Hou, JingXian Yu, ZhiZhu Lu, Xiao Zeng, QingQing Jia

“…The method incorporates a multi-scale temporal attention module and a multi-scale temporal convolution module to extract multi-scale information. …”
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Dynamic characteristic analysis and load design of large floating structures based on experimental design by Guofeng Zhao, Shifan Zhu

“…In order to make qualitative and quantitative analysis of the regularity, the hydrodynamic response of large-scale ocean engineering structures under different wave loads is experimentally designed and studied based on the experimental design method and the moving least squares–Kriging hybrid fitting method. …”
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UAV-to-Ground Target Detection Based on YOLO-DSBE by Meng Pengshuai, Wang Feng, Zhai Weiguang, Ma Xingyu, Zhao Wei

“…To address the issues of complex background, small target scale, mutual occlusion and high missed detection rate in UAV captured images, this paper proposes a ground target detection algorithm based on YOLO-DSBE.The DC-ELAN and DC-MP modules based on deformable convolution are proposed to adapt to input features of different shapes and sizes, and to improve the network’s ability to parse features in complex backgrounds; A high-resolution multi-scale detection layer is designed to boost the algorithm’s capability in extracting small target features, thereby improving the detection accuracy of minute targets. …”
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Research on semantic segmentation of parents in hybrid rice breeding based on improved DeepLabV3+ network model by WEN Jia, LIANG Xifeng, WANG Yongwei

“…Compared with other mainstream network models and advanced network models, it is found that the accuracy of different parameters of improved DeepLabV3+ network model is improved. …”
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Fish feeding behavior recognition model based on the fusion of visual and water quality features by Zheng ZHANG, Bosheng ZOU

“…To better capture the global features of different aggregation levels and the detailed features of feeding behavior, a context-aware local attention mechanism (Cloatt) was introduced in each convolution stage of ConvNeXtV2-T. …”
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Segmented Frequency-Domain Correlation Prediction Model for Long-Term Time Series Forecasting Using Transformer by Haozhuo Tong, Lingyun Kong, Jie Liu, Shiyan Gao, Yilu Xu, Yuezhe Chen

“…By segmenting the long-term time series and performing discrete Fourier transforms on different segments, we aim to identify frequency-domain correlations between these segments. …”
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An improved multi-object instance segmentation based on deep learning by Nawaf Alshdaifat, Mohd Azam Osman, Abdullah Zawawi Talib

“…The findings also revealed that in terms of average precision over IoU (AP) threshold measurements using different thresholds, the proposed approach obtained improved results compared to other well-known segmentation approaches. …”
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A lightweight and efficient gesture recognizer for traffic police commands using spatiotemporal feature fusion by Jun Xiao, Honghan Li, Ji Zhao

“…Initially, keypoints related to traffic police gestures are extracted using the Efficient Progressive Feature Fusion Network (EPFFNet), followed by feature modeling and fusion to enable the recognition network to better learn the temporal characteristics of gestures. Additionally, a convolution network branch and a hybrid attention branch are incorporated to further extract skeleton information from the traffic police gesture data, assign different temporal weights to key frames, and enhance the focus on important channels. …”
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Numerical solution of a spatio-temporal gender-structured model for hantavirus infection in rodents by Raimund BÜrger, Gerardo Chowell, Elvis GavilÁn, Pep Mulet, Luis M. Villada

“…The numerical results demonstrate significant differences in the spatio-temporal behavior predicted by the different models, which suggest future research directions.…”
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Complex Indoor Human Detection with You Only Look Once: An Improved Network Designed for Human Detection in Complex Indoor Scenes by Yufeng Xu, Yan Fu

“…The method proposed in this article combines the spatial pyramid pooling of the backbone with an efficient partial self-attention, enabling the network to effectively capture long-range dependencies and establish global correlations between features, obtaining feature information at different scales. At the same time, the GSEAM module and GSCConv were introduced into the neck network to compensate for the loss caused by differences in lighting levels by combining depth-wise separable convolution and residual connections, enabling it to extract effective features from visual data with poor illumination levels. …”
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Conflict between genetic and phenotypic differentiation: the evolutionary history of a 'lost and rediscovered' shorebird. by Frank E Rheindt, Tamás Székely, Scott V Edwards, Patricia L M Lee, Terry Burke, Peter R Kennerley, David N Bakewell, Monif Alrashidi, András Kosztolányi, Michael A Weston, Wei-Ting Liu, Wei-Pan Lei, Yoshimitsu Shigeta, Sálim Javed, Sama Zefania, Clemens Küpper

“…Alternatively, gene expression differences may be crucial in producing different phenotypes whereas neutral differentiation may be lagging behind.…”
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YOLO-UIR: A Lightweight and Accurate Infrared Object Detection Network Using UAV Platforms by Chao Wang, Rongdi Wang, Ziwei Wu, Zetao Bian, Tao Huang

“…Moreover, the LSP module efficiently combines features from different distances using Large Receptive Field Convolution Layers, significantly enhancing the model’s long-range information capture capability. …”
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