Improved YOLOv10n model for enhanced cotton recognition in complex environments by Yutao Gong, Wenwen Ding, Nenghui Huang, Tao Li, Juntao Zhou

“…To address this, this study improves the YOLOv10n model and proposes an enhanced YOLOv10n - based cotton recognition model.Firstly, the SimAM attention mechanism is integrated into the backbone network to strengthen the model's ability to focus on key features of multi - category cotton. Secondly, partial convolution (PConv) replaces standard convolution in the C2f module, creating a lightweight C2f - PConv structure to reduce computational redundancy.Test results indicate that the improved YOLOv10n model achieves 94 % detection accuracy, 89.7 % recall, and 94.8 % mAP@0.5. …”
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CGADNet: A Lightweight, Real-Time, and Robust Crosswalk and Guide Arrow Detection Network for Complex Scenes by Guangxing Wang, Tao Lin, Xiwei Dong, Longchun Wang, Qingming Leng, Seong-Yoon Shin

“…In this study, we incorporated a novel C2f_Van module based on VanillaBlock, employed depth-separable convolution to reduce the parameters efficiently, utilized partial convolution (PConv) for lightweight FasterDetect, and utilized a bounding box regression loss with a dynamic focusing mechanism—WIoU<i>_v3</i>—to enhance the detection performance. …”
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A Lightweight Citrus Object Detection Method in Complex Environments by Qiurong Lv, Fuchun Sun, Yuechao Bian, Haorong Wu, Xiaoxiao Li, Xin Li, Jie Zhou

“…First, to tackle the large size of the YOLOv7 network model and its deployment challenges, the PC-ELAN module is constructed by introducing Partial Convolution (PConv) for lightweight improvement, which reduces the model’s demand for computing resources and parameters. …”
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Certain Class of Analytic Functions Connected with q-Analogue of the Bessel Function by Nazek Alessa, B. Venkateswarlu, K. Loganathan, T.S. Karthik, P. Thirupathi Reddy, G. Sujatha

“…Furthermore, we discussed partial sums, convolution, and neighborhood properties for this defined class.…”
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Sines, transient, noise neural modeling of piano notes by Riccardo Simionato, Stefano Fasciani

“…The noise sub-module uses a learnable time-varying filter, and the transients are generated using a deep convolutional network. From singular notes, we emulate the coupling between different keys in trichords with a convolutional-based network. …”
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Distinguishing Difficulty Imbalances in Strawberry Ripeness Instances in a Complex Farmland Environment by Yang Gan, Xuefeng Ren, Huan Liu, Yongming Chen, Ping Lin

“…Therefore, we propose a novel model based on a hybrid attention mechanism. Firstly, a partial convolution-based compact inverted block is developed, which significantly enhances the feature extraction capability of the model. …”
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Research on a UAV-View Object-Detection Method Based on YOLOv7-Tiny by Yuyang Miao, Xihan Wang, Ning Zhang, Kai Wang, Lianhe Shao, Quanli Gao

“…Furthermore, incorporating the novel Partial_C_Detect detection head and Adaptive Kernel Convolution (AKConv) improves the detection capabilities for small and dynamically changing objects. …”
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Applying Fourier Neural Operator to insect wingbeat sound classification: Introducing CF-ResNet-1D by Béla J. Szekeres, Máté Natabara Gyöngyössy, János Botzheim

“…We introduce CF-ResNet-1D, a novel ResNet-inspired model that integrates Convolutional Fourier Layers, combining the strengths of FNOs and 1D-Convolutional processing. …”
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Local-non-local complementary learning network for 3D point cloud analysis by Ning Ye, Kaihao Feng, Sen Lin

“…To address this limitation, we propose the Local-Non-Local Complementary Learning Network (LNLCL-Net), a novel framework that enhances feature extraction and representation. Leveraging partial convolution, LNLCL-Net divides the feature map into distinct local and non-local components. …”
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Digital Synthesis of Sound Generated by Tibetan Bowls and Bells by Andrzej GOŁAŚ, Roman FILIPEK

“…A coupled mechanical-acoustic field described by partial differential equations was discretized by using the Finite Element Method (FEM) implemented in the ANSYS package. …”
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Graph attention networks based multi-agent path finding via temporal-spatial information aggregation. by Qingling Zhang, Peng Wang, Cui Ni, Xianchang Liu

“…Initially, historical observations are fused by incorporating a Gated Recurrent Unit (GRU) with a Convolutional Neural Network (CNN), extracting local observations to form an encoder. …”
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River floating object detection with transformer model in real time by Chong Zhang, Jie Yue, Jianglong Fu, Shouluan Wu

“…Further innovation is evident in the introduction of the Residual Partial Convolutional Network (RPCN) as the backbone, which selectively applies convolutions to key channels, leveraging the concept of residuals to reduce computational redundancy and enhance accuracy. …”
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YOLOv8-POS: a lightweight model for coal-rock image recognition by Yanqin Zhao, Wenyu Wang

“…The methodology introduces a C2f-PConv module, which ingeniously combines the strengths of C2f and partial convolution (PConv) to selectively process channels. …”
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Tomato ripeness detection and fruit segmentation based on instance segmentation by Jinfan Wei, Yu Sun, Yu Sun, Lan Luo, Lingyun Ni, Mengchao Chen, Minghui You, Minghui You, Ye Mu, Ye Mu, He Gong, He Gong

“…The method proposes two innovative modules: the Adaptive and Oriented Feature Refinement module (AOFRM) and the Custom Multi-scale Pooling module (CMPRD) with Residuals and Depth. By deformable convolution and multi-directional asymmetric convolution, the AOFRM module adaptively extracts the shape and direction features of tomatoes to solve the problems of occlusion and overlap. …”
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RDRM-YOLO: A High-Accuracy and Lightweight Rice Disease Detection Model for Complex Field Environments Based on Improved YOLOv5 by Pan Li, Jitao Zhou, Huihui Sun, Jian Zeng

“…We propose RDRM-YOLO, an enhanced YOLOv5-based network, integrating four key improvements: (i) a cross-stage partial network fusion module (Hor-BNFA) is integrated within the backbone network’s feature extraction stage to enhance the model’s ability to capture disease-specific features; (ii) a spatial depth conversion convolution (SPDConv) is introduced to expand the receptive field, enhancing the extraction of fine-grained features, particularly from small disease spots; (iii) SPDConv is also integrated into the neck network, where the standard convolution is replaced with a lightweight GsConv to increase the accuracy of disease localization, category prediction, and inference speed; and (iv) the WIoU Loss function is adopted in place of CIoU Loss to accelerate convergence and enhance detection accuracy. …”
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YOLO-MECD: Citrus Detection Algorithm Based on YOLOv11 by Yue Liao, Lerong Li, Huiqiang Xiao, Feijian Xu, Bochen Shan, Hua Yin

“…Secondly, we implemented a CSPPC module based on partial convolution to replace the original C3K2 module, effectively reducing both parameter count and computational complexity while maintaining mAP values. …”
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Research on multi-branch residual connection spectrum image classification based on attention mechanism by Zhong Xiaohui, Dong Sheng, Zhang Yiyi, Lu Wei, Jiang Lincen

“…Currently, the extensive use of convolutional neural networks for spectral image classification can extract signal features in the spectrogram, but the redundancy of noisy data generated by a large number of bands of the spectrum affects the feature information at different levels of the image. …”
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SYNTHESIS OF MOBILE OBJECTS COMPROMISABLE OPTIMAL TRAJECTORIES IN THE CONFLICT ENVIRONMENT by Albert M. Voronin, Yurii K. Ziatdinov, Oleksandr Y. Permiakov, Ihor D. Varlamov

“…In this regard, the problem of optimal movement trajectory synthesis under given conditions is solved by the dynamic programming method with optimality criterion obtained by as nonlinear compromise scheme scalar convolution. The generalized criterion consists of three particular criteria: the first defines the approach safety degree to the restricted zones borders, the second characterizes the transfer length, the third partial criterion defines the approach safety degree to the alien moving object.  …”
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Vibration under variable magnitude moving distributed masses of non-uniform Bernoulli-Euler beam resting on Pasternak elastic foundation by T. O. Awodola, S. A. Jimoh, B. B. Awe

“…The problem is governed by fourth-order partial differential equation with variable and singular coefficients. …”
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Quality prediction of air-cured cigar tobacco leaf using region-based neural networks combined with visible and near-infrared hyperspectral imaging by Jianxun Yin, Jun Wang, Jian Jiang, Jian Xu, Liang Zhao, Anfu Hu, Qian Xia, Zhihan Zhang, Ming Cai

“…Compared to Partial Least Squares Regression and Convolutional Neural Networks, DR-CNN demonstrated superior predictive accuracy, making it a promising model for quality prediction in cigar tobacco leaves during air-curing process. …”
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