AfaMamba: Adaptive Feature Aggregation With Visual State Space Model for Remote Sensing Images Semantic Segmentation by Hongkun Chen, Huilan Luo, Chanjuan Wang

“…It employs a lightweight ResNet18 as the encoder, and during the decoding phase, it first utilizes a multiscale feature adaptive aggregation module to ensure that the output features from each stage of the encoder contain rich multiscale semantic information. Subsequently, the global-local Mamba structure combines the attention-optimized multiscale convolutional branches with the global branch of Mamba to facilitate effective interaction between global and local features. …”
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Deep Learning Model for Precipitation Nowcasting Based on Residual and Attention Mechanisms by Zhan Zhang, Qingping Song, Minzheng Duan, Hailei Liu, Juan Huo, Congzheng Han

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WDM-UNet: A Wavelet-Deformable Gated Fusion Network for Multi-Scale Retinal Vessel Segmentation by Xinlong Li, Hang Zhou

“…To address these limitations, we propose WDM-UNet, a novel spatial-wavelet dual-domain fusion architecture that integrates spatial and wavelet-domain representations to simultaneously enhance the local detail and global context. The encoder combines a Deformable Convolution Encoder (DCE), which adaptively models complex vascular structures through dynamic receptive fields, and a Wavelet Convolution Encoder (WCE), which captures the semantic and structural contexts through low-frequency components and hierarchical wavelet convolution. …”
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Infrared object detection for robot vision based on multiple focus diffusion and task interaction alignment by Jixu Zhang, Li Wang, Hung-Wei Li, Meng-Yen Hsieh, Shunxiang Zhang, Hua Wen, Meng Chen

“…The feature extraction module adopts a dual-stream fusion structure in the backbone network, which combines the local feature extraction of CNN with the global feature modeling of transformer. …”
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DSS-MobileNetV3: An Efficient Dynamic-State-Space- Enhanced Network for Concrete Crack Segmentation by Haibo Li, Yong Cheng, Qian Zhang, Lingkun Chen

“…The DSS-MobileNetV3 adopts a U-shaped encoder–decoder architecture, and a dynamic-state-space (DSS) block is designed into the encoder to improve the MobileNetV3 bottleneck module in modeling global dependencies. The DSS block improves the MobileNetV3 model in structural perception and global dependency modeling for complex crack morphologies by integrating dynamic snake convolution and a state space model. …”
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A hybrid learning approach for MRI-based detection of alzheimer’s disease stages using dual CNNs and ensemble classifier by Sepideh Zolfaghari, Atra Joudaki, Yashar Sarbaz

“…Abstract Alzheimer’s Disease (AD) and related dementias are significant global health issues characterized by progressive cognitive decline and memory loss. …”
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CGD-CD: A Contrastive Learning-Guided Graph Diffusion Model for Change Detection in Remote Sensing Images by Yang Shang, Zicheng Lei, Keming Chen, Qianqian Li, Xinyu Zhao

“…However, most SSL algorithms for CD in remote sensing image rely on convolutional neural networks with fixed receptive fields as their feature extraction backbones, which limits their ability to capture objects of varying scales and model global contextual information in complex scenes. …”
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Lightweight human activity recognition method based on the MobileHARC model by Xingyu Gong, Xinyang Zhang, Na Li

“…However, due to the fact that these models have sequential network structures and are unable to simultaneously focus on local and global features, thus, resulting in a reduction in recognition performance. …”
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VM-UNet++ research on crack image segmentation based on improved VM-UNet by Wenliang Tang, Ziyi Wu, Wei Wang, Youqin Pan, Weihua Gan

“…Abstract Cracks are common defects in physical structures, and if not detected and addressed in a timely manner, they can pose a severe threat to the overall safety of the structure. …”
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InceptionDTA: Predicting drug-target binding affinity with biological context features and inception networks by Mahmood Kalemati, Mojtaba Zamani Emani, Somayyeh Koohi

“…InceptionDTA utilizes a multi-scale convolutional architecture based on the Inception network to capture features at various spatial resolutions, enabling the extraction of both local and global features from protein sequences and drug SMILES. …”
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Distinct brain age gradients across the adult lifespan reflect diverse neurobiological hierarchies by Nicholas Riccardi, Alex Teghipco, Sarah Newman-Norlund, Roger Newman-Norlund, Ida Rangus, Chris Rorden, Julius Fridriksson, Leonardo Bonilha

“…We address this gap by leveraging a data-driven, region-specific brain age approach in 335 neurologically intact adults, using a convolutional neural network (volBrain) to estimate regional brain ages directly from structural MRI without a predefined set of morphometric properties. …”
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An Effective Feature Extraction Method for Tomato Leafminer - Tuta Absoluta (Meyrick) (Lepidoptera: Gelechiidae) Classification by Tahsin Uygun, Serhat Kiliçarslan, Cemil Közkurt, Mehmet Metin Ozguven

“…Abstract Global warming caused by climate change causes some problems in agricultural production. …”
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Leveraging artificial intelligence for diagnosis of children autism through facial expressions by Mahmood A. Mahmood, Leila Jamel, Nazik Alturki, Medhat A. Tawfeek

“…Abstract The global population contains a substantial number of individuals who experience autism spectrum disorder, thus requiring immediate identification to enable successful intervention approaches. …”
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Transformer-based ensemble model for dialectal Arabic sentiment classification by Omar Mansour, Eman Aboelela, Remon Talaat, Mahmoud Bustami

“…The complexity arises from the language’s intricate semantic and morphological structures, along with the existence of multiple dialects. …”
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Breast cancer classification based on hybrid CNN with LSTM model by Mourad Kaddes, Yasser M. Ayid, Ahmed M. Elshewey, Yasser Fouad

“…Abstract Breast cancer (BC) is a global problem, largely due to a shortage of knowledge and early detection. …”
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TDFNet: twice decoding V-Mamba-CNN Fusion features for building extraction by Wenlong Wang, Peng Yu, Mengmeng Li, Xiaojing Zhong, Yuanrong He, Hua Su, Yunxuan Zhou

“…A bidirectional fusion module (BFM) is then designed to comprehensively integrate spatial details and global information, thereby enabling accurate identification of boundaries between adjacent buildings, and maintaining the structural integrity of buildings to avoid internal holes. …”
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A New and Tested Ionospheric TEC Prediction Method Based on SegED-ConvLSTM by Yuanhang Liu, Yingkui Gong, Hao Zhang, Ziyue Hu, Guang Yang, Hong Yuan

“…Accurate prediction of TEC plays a crucial role in improving the precision of Global Navigation Satellite Systems (GNSS). However, existing research have predominantly emphasized spatial variations in the ionosphere, neglecting the periodic changes of the ionosphere with the diurnal cycle. …”
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DRDA-Net: Deep Residual Dual-Attention Network with Multi-Scale Approach for Enhancing Liver and Tumor Segmentation from CT Images by Wail M. Idress, Yuqian Zhao, Khalid A. Abouda, Shaodi Yang

“…Additionally, we introduce a unique pre-processing pipeline employing a two-channel denoising technique using convolutional neural networks (CNNs) and stationary wavelet transforms (SWTs) to reduce noise while preserving structural details. …”
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Financial accounting management strategy based on business intelligence technology for sustainable development strategy by Jianben Feng

“…The model firstly transforms the corporate financial data into graph structure, and extracts the features of complex financial relationships through graph convolutional neural network, and at the same time combines with the dynamic time regularization method to enhance the adaptability to the dynamic change of time. …”
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Applying SSVEP BCI on Dynamic Background by Junkai Li, Boxun Fu, Fu Li, Wenkai Gu, Youshuo Ji, Yang Li, Tiejun Liu, Guangming Shi

“…MTSGNN is built with efficient convolutional structures and uses global average pooling to achieve classification, which effectively reduces the risk of model overfitting on small EEG datasets and improves classification performance. …”
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