FFLKCDNet: First Fusion Large-Kernel Change Detection Network for High-Resolution Remote Sensing Images by Bochao Chen, Yapeng Wang, Xu Yang, Xiaochen Yuan, Sio Kei Im

“…This paper proposes a high-resolution remote sensing image change detection model called FFLKCDNet (First Fusion Large-Kernel Change Detection Network) to solve this issue. FFLKCDNet features a Bi-temporal Feature Fusion Module (BFFM) to fuse remote sensing features from different temporal scales, and an improved ResNet network (RAResNet) that combines large-kernel convolution and multi-attention mechanisms to enhance feature extraction. …”
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A Crowd Counting and Localization Network Based on Adaptive Feature Fusion and Multi-Scale Global Attention Up Sampling by Min Wang, Li Huang, Jingke Yan, Jin Huang, Tao Yang

“…By avoiding the problem of overlap in dense areas, the optimized label maps achieve a good balance between counting accuracy and localization, with MAE and MSE reaching 64.1 and 103.9 in SHHA, and 10.9 and 17.4 in SHHB, respectively.Secondly, to address the scale insensitivity of the encoder and the potential loss of critical features during the encoding process, we propose the Adaptive Feature Fusion Module and the Multi-Scale Global Attention Upsampling Module, constructing the CALNET network. …”
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A simple monocular depth estimation network for balancing complexity and accuracy by Xuanxuan Liu, Shuai Tang, Mengdie Feng, Xueqi Guo, Yanru Zhang, Yan Wang

“…For the extraction of finer local features, we propose a Local Multi-dimensional Convolutional Attention (LMC) module. Meanwhile, we propose a Wavelet Attention Transformer (WAT) module to achieve pixel-level precise classification of images. …”
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Detecting Planting Holes Using Improved YOLO-PH Algorithm with UAV Images by Kaiyuan Long, Shibo Li, Jiangping Long, Hui Lin, Yang Yin

“…Compared to the YOLOv8 network, the proposed YOLO-PH network incorporates the C2f_DyGhostConv module as a replacement for the original C2f module in both the backbone network and neck network. …”
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A Novel Transformer-Based Multiscale Siamese Framework for High-Resolution Remote Sensing Change Detection by Liangjun Wang, Weitao Chen, Haoyi Wang, Zhengchao Chen

“…To resolve the aforementioned issue, we propose a transformer-based multiscale Siamese framework (TMSF) for high-resolution remote sensing CD, aiming to improve detection accuracy. …”
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ACGNet: An Alternating Conjugate Gradient Optimization-Based Neural Network for SAR Image Despeckling by Xin Mao, Ying Liu, Chenghao Qiu, Cong Lin

“…In addition, to enhance the feature learning capability of the denoising network, a dynamic edge-guided attention module is introduced. This module enhances feature learning capability and improves image detail extraction by guiding network decision making through adaptive weights. …”
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Hybrid attentive prototypical network for few-shot action recognition by Zanxi Ruan, Yingmei Wei, Yanming Guo, Yuxiang Xie

“…We further propose a prototypical attentive matching module (PAM) built on the concept of metric learning to resolve the overfitting issue common in few-shot tasks. …”
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CenterNet-Elite: A Small Object Detection Model for Driving Scenario by Lingling Wang, Xiang Li, Xiaoyan Chen, Bin Zhou

“…We introduce a multi-scale pooling module, SPPCSPC, to address the challenge of significant variations in object scale. …”
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LMSOE-Net: lightweight multi-scale small object enhancement network for UAV aerial images by Zhixing Ma, Peidong Luo, Xiaole Shen

“…Additionally, we replace the Spatial Pyramid Pooling Fast (SPPF) module in YOLOv8 with the Feature Pyramid Shared Convolution (FPSC) module. …”
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ELNet: An Efficient and Lightweight Network for Small Object Detection in UAV Imagery by Hui Li, Jianbo Ma, Jianlin Zhang

“…First, based on an analysis of UAV image characteristics, we strategically remove two A2C2f modules from YOLOv12n and adjust the size and number of detection heads. …”
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Video Instance Segmentation Through Hierarchical Offset Compensation and Temporal Memory Update for UAV Aerial Images by Ying Huang, Yinhui Zhang, Zifen He, Yunnan Deng

“…Firstly, a hierarchical offset compensation (HOC) module in the form of a sequential and parallel connection is designed to perform deformable offset for the same flexible target across frames, which benefits from compensating for spatial motion features at the time sequence. …”
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AFN-Net: Adaptive Fusion Nucleus Segmentation Network Based on Multi-Level U-Net by Ming Zhao, Yimin Yang, Bingxue Zhou, Quan Wang, Fu Li

“…Therefore, a novel nucleus segmentation method based on the U-Net architecture is proposed to overcome this issue. Firstly, we introduce a Weighted Feature Enhancement Unit (WFEU) in the encoder decoder fusion stage of U-Net. …”
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SVD-Based Feature Reconstruction Metric Network With Active Contrast Loss for Few-Shot SAR Target Recognition by Jia Zheng, Ming Li, Xiang Li, Peng Zhang, Yan Wu

“…However, in practical SAR applications, the scarcity of samples has always been a persistent issue, especially in the military domain, where certain target types may have very few samples. …”
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EDG-Net: Edge-Enhanced Dynamic Graph Convolutional Network for Remote Sensing Scene Classification of Mining-Disturbed Land by Xianju Li, Pan Kong, Weitao Chen, Wenxi He, Jian Feng, Jiangyuan Wang

“…Subsequently, a novel model of edge-enhanced dynamic graph convolutional network (GCN) (EDG-Net) was proposed to learn the discriminative features for classification of mining land with irregular edges, different sizes, a relatively small proportion, and sparse spatial distribution. (1) Edge-enhanced multiscale attention module: it is designed to capture key multiscale features and edge details using parallel dilated convolutions with attention fusion and edge enhancement, which facilitates the identification of objects with irregular edges and different sizes. (2) Downsampling fusion module: it integrates the features obtained through spatially split learning and max-pooling to overcome the information loss issue of small objects. (3) Patch-based dynamic GCN: the input images were split into several patches as nodes, and a graph was constructed and dynamically updated by connecting the nearest neighbors. …”
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Deep Learning-Based Instance Segmentation of Galloping High-Speed Railway Overhead Contact System Conductors in Video Images by Xiaotong Yao, Huayu Yuan, Shanpeng Zhao, Wei Tian, Dongzhao Han, Xiaoping Li, Feng Wang, Sihua Wang

“…When combined with the galloping visualization module, it can issue real-time alerts of conductor galloping anomalies, providing robust technical support for railway OCS safety monitoring.…”
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Sistem Pendeteksi Central Sleep Apnea Menggunakan Metode Neural Network dengan Fitur RR Interval dan Durasi QRS by Dittha Ratanasari, Edita Rosana Widasari, Rizal Maulana

“…Sistem dirancang dengan mikrokontroller Arduino Uno, sensor AD8232 dan modul Bluetooth HC-05. Sensor sebagai pendeteksi aktifitas listrik jantung, dengan 3 buah elektroda menempel pada dada untuk merekam lalu diekstraksi fitur RR interval dan durasi QRS. …”
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Identification of the key material degradation mechanisms affecting silicon solar cells: Systematic literature review by Eshetu Tadesse Ymer, Hirpa Gelgele Lemu, Mesay Alemu Tolcha

“…In conclusion, this review underscores the necessity of climate-specific module designs and tailored maintenance strategies, such as the implementation of PID-resistant cells and anti-soiling coatings, to significantly enhance PV durability. …”
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CFAR-DP-FW: A CFAR-Guided Dual-Polarization Fusion Framework for Large-Scene SAR Ship Detection by Tianjiao Zeng, Tianwen Zhang, Zikang Shao, Xiaowo Xu, Wensi Zhang, Jun Shi, Shunjun Wei, Xiaoling Zhang

“…The proposed CFAR-DP-FW consists of three core components: the CFAR dual-polarization detector provides initial target indication; the CFAR field generator constructs a probabilistic ship presence map, reducing reliance on CFAR's hard thresholds; and the CFAR guidance dual-polarization network incorporates a novel feature extractor and enhancement module, tailored to amplify relevant features, and suppress noise. …”
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On Dracograllus miguelitus sp. nov. (Nematoda: Draconematidae) from an inactive structure: insights into its taxonomy, biodiversity and ecology at hydrothermal vents by William Johnson da Silva, Daniela Zeppilli, Valentin Foulon, Pierre-Antoine Dessandier, Marjolaine Matabos, Jozee Sarrazin

“…Fluorescent images were obtained using the ApoTome Fluorescence Microscope Module, and 3D observations were possible through the depth change method. …”
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Development of a GPT-4–Powered Virtual Simulated Patient and Communication Training Platform for Medical Students to Practice Discussing Abnormal Mammogram Results With Patients: M... by Dan Weisman, Alanna Sugarman, Yue Ming Huang, Lillian Gelberg, Patricia A Ganz, Warren Scott Comulada

“…A formative phase with in-depth knowledge user interviews informed development, followed by a development phase to create the virtual training module. The team conducted interviews with 5 medical students, 5 PCPs, and 5 breast cancer survivors. …”
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