DASNet a dual branch multi level attention sheep counting network by Yini Chen, Ronghua Gao, Qifeng Li, Hongtao Zhao, Rong Wang, Luyu Ding, Xuwen Li

“…The varying flight altitudes, diverse scenes, and different density levels captured by the drones endow our dataset with a high degree of diversity. …”
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A Quality Soft Sensing Method Designed for Complex Multi-process Manufacturing Procedures by Kaixiang PENG, Xin QIN, Jiahao WANG, Hui YANG

“…For each procedure, the time delay effect between different procedure segments and quality variables is considered, and data alignment is performed. …”
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Cardioattentionnet: advancing ECG beat characterization with a high-accuracy and portable deep learning model by Youfu He, Youfu He, Youfu He, Yu Zhou, Yu Zhou, Yu Qian, Jingjie Liu, Jinyan Zhang, Debin Liu, Qiang Wu, Qiang Wu

“…CANet integrates Bi-directional Long Short-Term Memory (BiLSTM) networks, Multi-head Attention mechanisms, and Depthwise Separable Convolution, thereby facilitating its application in portable devices for early diagnosis. …”
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Large N limit of the Yang–Mills measure on compact surfaces II: Makeenko–Migdal equations and the planar master field by Antoine Dahlqvist, Thibaut Lemoine

“…Our result on the torus justifies the introduction of an interpolation between free and classical convolution of probability measures, defined with the free unitary Brownian motion but differing from t-freeness of [5] that was defined in terms of the liberation process of Voiculescu [67]. …”
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Deep Learning-Based Speech Emotion Recognition Using Multi-Level Fusion of Concurrent Features by Samuel, Kakuba, Alwin, Poulose, Dong, Seog Han, Senior Member, Ieee

“…There are complex relationships between the extracted features at different time intervals which ought to be analyzed to infer the emotions in speech. …”
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Image restoration using a discrete point spread function with consideration of finite pixel size by Victor B. Fedorov, Sergey G. Kharlamov, Alexey V. Fedorov

“…A common approach to this problem involves solving the Fredholm integral equation of the first convolution type by means of discretization based on quadrature formulas. …”
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Custom Network Quantization Method for Lightweight CNN Acceleration on FPGAs by Lingjie Yi, Xianzhong Xie, Yi Wan, Bo Jiang, Junfan Chen

“…Additionally, following network quantization, the differences in data types between the operators can cause issues when deploying networks on Field Programmable Gate Arrays (FPGAs). …”
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Leveraging two-dimensional pre-trained vision transformers for three-dimensional model generation via masked autoencoders by Muhammad Sajid, Kaleem Razzaq Malik, Ateeq Ur Rehman, Tauqeer Safdar Malik, Masoud Alajmi, Ali Haider Khan, Amir Haider, Seada Hussen

“…In vision, attention is used in conjunction with convolutional networks or to replace individual convolutional network elements while preserving the overall network design. …”
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A Novel Dual-Branch Pansharpening Network with High-Frequency Component Enhancement and Multi-Scale Skip Connection by Wei Huang, Yanyan Liu, Le Sun, Qiqiang Chen, Lu Gao

“…Second, to address the differences, the low-frequency branch consists of the multi-scale skip connection module (MSSCM), which comprehensively captures the multi-scale features from coarse to fine through multi-scale convolution, and it effectively fuses these multilevel features through the designed skip connection mechanism to fully extract the low-frequency information from MS and PAN images. …”
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Cross-Visual Style Change Detection for Remote Sensing Images via Representation Consistency Deep Supervised Learning by Jinjiang Wei, Kaimin Sun, Wenzhuo Li, Wangbin Li, Song Gao, Shunxia Miao, Yingjiao Tan, Wei Cui, Yu Duan

“…Change detection techniques, which extract different regions of interest from bi-temporal remote sensing images, play a crucial role in various fields such as environmental protection, damage assessment, and urban planning. …”
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EHAFF-NET: Enhanced Hybrid Attention and Feature Fusion for Pedestrian ReID by Jun Yang, Yan Wang, Haizhen Xie, Jiayue Chen, Shulong Sun, Xiaolan Zhang

“…This study addresses the cross-scenario challenges in pedestrian re-identification for public safety, including perspective differences, lighting variations, occlusions, and vague feature expressions. …”
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UCrack-DA: A Multi-Scale Unsupervised Domain Adaptation Method for Surface Crack Segmentation by Fei Deng, Shaohui Yang, Bin Wang, Xiujun Dong, Siyuan Tian

“…Additionally, by integrating a Mix-Transformer encoder, a multi-scale dilated attention module, and a mixed convolutional attention decoder, we effectively solve the challenges of cross-domain data distribution differences and complex scene crack segmentation. …”
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Multilevel Feature Cross-Fusion-Based High-Resolution Remote Sensing Wetland Landscape Classification and Landscape Pattern Evolution Analysis by Sijia Sun, Biao Wang, Zhenghao Jiang, Ziyan Li, Sheng Xu, Chengrong Pan, Jun Qin, Yanlan Wu, Peng Zhang

“…To address these issues, this study proposes the multilevel feature cross-fusion wetland landscape classification network (MFCFNet), which combines the global modeling capability of Swin Transformer with the local detail-capturing ability of convolutional neural networks (CNNs), facilitating discerning intraclass consistency and interclass differences. …”
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AttenCRF-U: Joint Detection of Sleep-Disordered Breathing and Leg Movements in OSA Patients by Qiuyue Li, Kewei Li, Cong Fu, Yiyuan Zhang, Huan Yu, Chen Chen, Wei Chen

“…Traditional single-event detection methods often overlook the dynamic interactions between SDB and LM, failing to capture their temporal overlap and differences in duration. To address this, we propose Attention-enhanced CRF with U-Net (AttenCRF-U), a novel joint detection framework that integrates multi-head self-attention (MHSA) within an encoder–decoder architecture to model long-range dependencies between overlapping events and employs multi-scale convolutional encoding to extract discriminative features across different temporal scales. …”
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Real-Time Multi-Task Deep Learning Model for Polyp Detection, Characterization, and Size Estimation by Phanukorn Sunthornwetchapong, Kasichon Hombubpha, Kasenee Tiankanon, Satimai Aniwan, Pasit Jakkrawankul, Natawut Nupairoj, Peerapon Vateekul, Rungsun Rerknimitr

“…In this work, we present a modified convolutional neural network (CNN) based deep learning (DL) model to perform these tasks in real-time, utilizing existing object detection models: YOLOv5 and YOLOv8. …”
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Optimized Motion Capture for Cricket Shot Classification Using Minimal Hardware and Machine Learning by J. Ishan Randika, Kanishka Rajamanthri, Avishka Kothalawala, Niroshan Gunawardana, Ashan Induranga, Pathum Weerakkody, Kaveendra Maduwantha, B. T. G. S. Kumara, Kaveenga Koswattage

“…Motion data collected from the system was analyzed to extract distinct angle variation patterns associated with different batting shots. These patterns were used to train a hybrid machine learning model combining Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks. …”
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Vision Foundation Model Guided Multimodal Fusion Network for Remote Sensing Semantic Segmentation by Chen Pan, Xijian Fan, Tardi Tjahjadi, Haiyan Guan, Liyong Fu, Qiaolin Ye, Ruili Wang

“…The fusion of multimodal data presents challenges due to discrepancies in image acquisition mechanisms among different sensors, leading to misalignment issues. …”
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STID-Net: Optimizing Intrusion Detection in IoT with Gradient Descent by James Deva Koresh Hezekiah, Usha Nandini Duraisamy, Kalaichelvi Nallusamy, Avudaiammal Ramalingam, Saranya Chandran, Murugesan Rajeswari Thiyagupriyadharsan, Periasamy Selvaraju, Rajagopal Maheswar

“…Existing methods often struggle in capturing complex and irregular patterns from dynamic intrusion data, making them not suitable for different IoT applications. To address these limitations, this work proposes STID-Net that integrated customized convolutional kernels for spatial feature extraction and LSTM layers for temporal sequence modelling. …”
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Temporal waveform denoising using deep learning for injection laser systems of inertial confinement fusion high-power laser facilities by Wei Chen, Xinghua Lu, Wei Fan, Xiaochao Wang

“…For the pulse shaping system of the SG-II-up facility, we propose a U-shaped convolutional neural network that integrates multi-scale feature extraction capabilities, an attention mechanism and long short-term memory units, which effectively facilitates real-time denoising of diverse shaping pulses. …”
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Hybrid-KANet: a hyperspectral remote sensing crop classification method based on the Kolmogorov–Arnold network by Weizhen Zhang, Zhihui Li, Tong Zhen

“…The ablation experiments demonstrate the advantages of RBF kernel function in modeling complex nonlinear relationships by systematically comparing the differences in classification performance and boundary modeling ability of different kernel functions, which improves the classification accuracy and spatial consistency. …”
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