SMM-POD: Panoramic 3D Object Detection via Spherical Multi-Stage Multi-Modal Fusion by Jinghan Zhang, Yusheng Yang, Zhiyuan Gao, Hang Shi, Yangmin Xie

“…A cross-attention-based feature extraction module and a transformer encoder–decoder with spherical positional encoding enable the accurate and efficient fusion of image and point cloud features. …”
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Attention activation network for bearing fault diagnosis under various noise environments by Yu Zhang, Lianlei Lin, Junkai Wang, Wei Zhang, Sheng Gao, Zongwei Zhang

“…Proactive monitoring and diagnosing of bearing faults can prevent significant safety issues. Among various diagnostic methods that analyze bearing vibration signals, deep learning is notably effective. …”
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MSF-ACA: Low-Light Image Enhancement Network Based on Multi-Scale Feature Fusion and Adaptive Contrast Adjustment by Zhesheng Cheng, Yingdan Wu, Fang Tian, Zaiwen Feng, Yan Li

“…To address the issues of loss of important detailed features, insufficient contrast enhancement, and high computational complexity in existing low-light image enhancing methodologies, this paper presents a low-light image enhancement network (MSF-ACA), which uses multi-scale feature fusion and adaptive contrast adjustment. …”
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Efficient Attention Transformer Network With Self-Similarity Feature Enhancement for Hyperspectral Image Classification by Yuyang Wang, Zhenqiu Shu, Zhengtao Yu

“…Furthermore, we design two efficient feature extraction modules based on the preprocessed patches, called spectral interactive transformer module and spatial conv-attention module, to reduce the computational costs of the classification framework. …”
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BurgsVO: Burgs-Associated Vertex Offset Encoding Scheme for Detecting Rotated Ships in SAR Images by Mingjin Zhang, Yaofei Li, Jie Guo, Yunsong Li, Xinbo Gao

“…BurgsVO consists of two key modules: the Burgs equation heuristics module, which facilitates feature extraction, and the average diagonal vertex offset (ADVO) encoding scheme, which significantly reduces computational costs. …”
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Landslide susceptibility assessment using lightweight dense residual network with emphasis on deep spatial features by Shenghua Xu, Zhuolu Wang, Jiping Liu, Xinrui Ma, Tingting Zhou, Qing Tang

“…To minimize computational costs, we design a depthwise separable residual module that optimizes traditional convolution on residual branches into depthwise separable convolution. …”
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DAPONet: A Dual Attention and Partially Overparameterized Network for Real-Time Road Damage Detection by Weichao Pan, Jianmei Lei, Xu Wang, Chengze Lv, Gongrui Wang, Chong Li

“…DAPONet proposes three main innovations: (1) a dual attention mechanism that combines global context and local attention, (2) a multi-scale partial overparameterization module (CPDA), and (3) an efficient downsampling module (MCD). …”
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Remote Sensing Image Dehazing via Dual-View Knowledge Transfer by Lei Yang, Jianzhong Cao, He Bian, Rui Qu, Huinan Guo, Hailong Ning

“…The DVKT framework includes two novel knowledge-transfer modules: Intra-layer Transfer (Intra-KT) and Inter-layer Knowledge Transfer (Inter-KT) modules. …”
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Anomaly detection in multidimensional time series for water injection pump operations based on LSTMA-AE and mechanism constraints by Mei Wang, Xinyuan Zhu, Guangyue Zhou, Kewen Li, Qingshan Wu, Wankai Fan

“…The LSTMA-AE framework encompasses three primary modules: a Time Feature Extraction Module (Encoder), an Attention Layer, and a Data Reconstruction Module (Decoder). …”
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YOLOv8-TEA: Recognition Method of Tender Shoots of Tea Based on Instance Segmentation Algorithm by Wenbo Wang, Yidan Xi, Jinan Gu, Qiuyue Yang, Zhiyao Pan, Xinzhou Zhang, Gongyue Xu, Man Zhou

“…Firstly, this algorithm is based on the single-stage instance segmentation algorithm YOLOv8-seg, replacing some C2f modules in the original feature extraction network with MVB, combining the advantages of convolutional neural networks (CNN) and Transformers, and adding a C2PSA module following spatial pyramid pooling (SPPF) to integrate convolution and attention mechanisms. …”
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MCRFS-Net: single image dehazing based on multi-scale contrastive regularization and frequency selection by Qin Qin, Lin Shui, Yanyan Zhang, Shaojing Song, Jinhua Jiang

“…To overcome this limitation, this paper introduces a novel Adaptive Multi-Scale Frequency Selection (AMFS) module, which consists of an Adaptive Multi-Scale Module (AMSM) and a Frequency Selection Block (FSB). …”
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ACNet: An Attention–Convolution Collaborative Semantic Segmentation Network on Sensor-Derived Datasets for Autonomous Driving by Qiliang Zhang, Kaiwen Hua, Zi Zhang, Yiwei Zhao, Pengpeng Chen

“…Although deep learning methods have made significant progress, two main challenges remain: first, the difficulty in balancing global and local features leads to blurred object boundaries and misclassification; second, conventional convolutions have limited ability to perceive irregular objects, causing information loss and affecting segmentation accuracy. To address these issues, this paper proposes a global–local collaborative attention module and a spider web convolution module. …”
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Enhancing, Refining, and Fusing: Towards Robust Multiscale and Dense Ship Detection by Congxia Zhao, Xiongjun Fu, Jian Dong, Shen Cao, Chunyan Zhang

“…CASS-Det integrates three key innovations: 1) a center enhancement module (CEM) that employs rotational convolution to emphasize ship centers, improving localization while suppressing background interference; 2) a neighbor attention module that leverages cross-layer dependencies to refine ship boundaries in densely populated scenes; and 3) a cross-connected feature pyramid network (CC-FPN) that enhances multiscale feature fusion by integrating shallow and deep features. …”
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A modality separation approach for facial sketch synthesis by Kangning Du, Chaoyi Wang, Lin Cao, Yanan Guo, Wenwen Sun

“…Next, an edge‐promoting module feeds processed blurry sketch images into the discriminator to enhance robustness. …”
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Rotation-Invariant Feature Enhancement with Dual-Aspect Loss for Arbitrary-Oriented Object Detection in Remote Sensing by Zhao Hu, Xiangfu Meng, Xinsong Liu, Zhuxiang Sun

“…Furthermore, a rotation feature fusion (RFF) module propagates these rotation-aware features across hierarchical levels through an attention-guided fusion strategy, resulting in richer, more discriminative representations at multiple scales. …”
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LBT-YOLO: A Lightweight Road Targeting Algorithm Based on Task Aligned Dynamic Detection Heads by Pei Tang, Zhenyu Ding, Minnan Jiang, Weikai Xu, Mao Lv

“…Autonomous driving technology plays a key role in addressing traffic safety issues and relieving traffic congestion by virtue of its capabilities of enabling accurate environmental perception and real-time response. …”
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EMHANet: Lightweight Salient Object Detection for Remote Sensing Images via Edge-Aware Multiscale Feature Fusion by Qian Tang, Zhen Wang, Xuqi Wang, Shan-Wen Zhang

“…EMHANet consists of MobileNetV3 for feature extraction, an Edge Feature Integration Module (EFIM) for low-level edge details, a Multi-scale Contextual Information Enhancement Module (MCIEM) for high-level feature refinement, and a lightweight decoder for saliency prediction. …”
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Robust UAV Tracking via Information Synergy Fusion and Multi-Dimensional Spatial Perception by Yong Lin, Mingfeng Yin, Yingjie Zhang, Xiaoteng Guo

“…Then, a multi-dimensional spatial perception (MSP) module is constructed to compute global dependencies and spatial dependency information during the tracking phase, which aggregates target feature information from different scales. …”
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Face Forgery Detection with Long-Range Noise Features and Multilevel Frequency-Aware Clues by Yi Zhao, Xin Jin, Song Gao, Liwen Wu, Shaowen Yao, Qian Jiang

“…The widespread dissemination of high-fidelity fake faces created by face forgery techniques has caused serious trust concerns and ethical issues in modern society. Consequently, face forgery detection has emerged as a prominent topic of research to prevent technology abuse. …”
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Multiscale Hyperspectral Pansharpening Network Based on Dual Pyramid and Transformer by Hengyou Wang, Jie Zhang, Lian-Zhi Huo

“…However, most existing deep learning-based pansharpening methods have some issues, such as spectral distortion and insufficient spatial texture enhancement. …”
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