Bearing fault diagnosis based on efficient cross space multiscale CNN transformer parallelism by Qi Chen, Feng Zhang, Yin Wang, Qing Yu, Genfeng Lang, Lixiong Zeng

“…Subsequently, parallel branches are employed to extract spatio-temporal features: the Convolutional Neural Network (CNN) branch integrates a multiscale feature extraction module, a Reversed Residual Structure (RRS), and an Efficient Multiscale Attention (EMA) mechanism to enhance local and global feature extraction capabilities; the Transformer branch combines Bidirectional Gated Recurrent Units (BiGRU) and Transformer to capture both local temporal dynamics and long-term dependencies. …”
Get full text

Extensive identification of landslide boundaries using remote sensing images and deep learning method by Chang-dong Li, Peng-fei Feng, Xi-hui Jiang, Shuang Zhang, Jie Meng, Bing-chen Li

“…SCDnn exhibits notable improvements in landslide feature extraction and semantic segmentation by combining an enhanced Atrous Spatial Pyramid Convolutional Block (ASPC) with a coding structure that reduces model complexity. …”
Get full text

YOLOv8n-WSE-Pest: A Lightweight Deep Learning Model Based on YOLOv8n for Pest Identification in Tea Gardens by Hongxu Li, Wenxia Yuan, Yuxin Xia, Zejun Wang, Junjie He, Qiaomei Wang, Shihao Zhang, Limei Li, Fang Yang, Baijuan Wang

“…The addition of the Spatial and Channel Reconstruction Convolution structure in the Backbone layer reduces redundant spatial and channel features, thereby reducing the model’s complexity. …”
Get full text

GHFormer-Net: Towards more accurate small green apple/begonia fruit detection in the nighttime by Meili Sun, Liancheng Xu, Rong Luo, Yuqi Lu, Weikuan Jia

“…Specifically, PVTv2-B1 based on Transformer is applied as the backbone network to extract feature information from the global receptive, which breaks the limitation that spatial convolution is utilized to extract information from the local area; Next, with the help of FPN, shallow features and high-level features with rich semantic information are incorporated by lateral connections and a top-down structure to generate multi-scale feature maps; Then, a detector of RetinaNet is applied to detect green fruits. …”
Get full text

Research on CTSA-DeepLabV3+ Urban Green Space Classification Model Based on GF-2 Images by Ruotong Li, Jian Zhao, Yanguo Fan

“…As an important part of urban ecosystems, urban green spaces play a key role in ecological environmental protection and urban spatial structure optimization. However, due to the complex morphology and high degree of fragmentation of urban green spaces, it is still challenging to effectively distinguish urban green space types from high spatial resolution images. …”
Get full text

Modeling energy consumption indexes of an industrial cement ball mill for sustainable production by Saeed Chehreh Chelgani, Rasoul Fatahi, Ali Pournazari, Hamid Nasiri

“…Abstract The total cement energy consumption is around 5% of global industrial energy usage. In cement plants, mills consume half of this energy for dry grinding particles. …”
Get full text

Dynamic Ensemble Selection for EEG Signal Classification in Distributed Data Environments by Małgorzata Przybyła-Kasperek, Jakub Sacewicz

“…Additionally, we tested a convolutional neural network specifically designed for EEG data, ensuring our results are compared against advanced deep learning methods. …”
Get full text

Lightweight Road Environment Segmentation using Vector Quantization by J. Kwag, A. Yilmaz, C. Toth

“…Numerous works based on Fully Convolutional Networks (FCNs) and Transformer architectures have been proposed to leverage local and global contextual learning for efficient and accurate semantic segmentation. …”
Get full text

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

“…DASNet is built on a modified VGG–19 architecture, where a dual-branch structure is employed to integrate both shallow and deep features. …”
Get full text

Liver Semantic Segmentation Method Based on Multi-Channel Feature Extraction and Cross Fusion by Chenghao Zhang, Lingfei Wang, Chunyu Zhang, Yu Zhang, Peng Wang, Jin Li

“…Secondly, an atrous spatial pyramid pooling (ASPP) module is incorporated into the bottleneck layer to capture features at various receptive fields using dilated convolutions, while global pooling is applied to enhance the acquisition of contextual information and ensure efficient feature transmission. …”
Get full text

GhostConv+CA-YOLOv8n: a lightweight network for rice pest detection based on the aggregation of low-level features in real-world complex backgrounds by Fei Li, Yang Lu, Qiang Ma, Shuxin Yin, Rui Zhao

“…To overcome these limitations, this paper introduces GhostConv+CA-YOLOv8n, a lightweight object detection framework was proposed, which incorporates several innovative features: GhostConv replaces standard convolutional operations with computationally efficient ghost modules in the YOLOv8n’s backbone structure, reducing parameters by 40,458 while maintaining feature richness; a Context Aggregation (CA) module is applied after the large and medium-sized feature maps were output by the YOLOv8n’s neck structure. …”
Get full text

SCCA-YOLO: Spatial Channel Fusion and Context-Aware YOLO for Lunar Crater Detection by Jiahao Tang, Boyuan Gu, Tianyou Li, Ying-Bo Lu

“…Specifically, the Context-Aware Module (CAM) employs a multi-branch dilated convolutional structure to enhance feature richness and expand the local receptive field, thereby strengthening the feature extraction capability. …”
Get full text

Rice Disease Detection: TLI-YOLO Innovative Approach for Enhanced Detection and Mobile Compatibility by Zhuqi Li, Wangyu Wu, Bingcai Wei, Hao Li, Jingbo Zhan, Songtao Deng, Jian Wang

“…As a key global food reserve, rice disease detection technology plays an important role in promoting food production, protecting ecological balance and supporting sustainable agricultural development. …”
Get full text

RMIS-Net: a fast medical image segmentation network based on multilayer perceptron by Binbin Zhang, Guoliang Xu, Yiying Xing, Nanjie Li, Deguang Li

“…To address the persistent challenges of computational complexity and efficiency limitations in existing methods, we propose RMIS-Net—an innovative lightweight segmentation network with three core components: a convolutional layer for preliminary feature extraction, a shift-based fully connected layer for parameter-efficient spatial modeling, and a tokenized multilayer perceptron for global context capture. …”
Get full text

Novel Deep Learning Framework for Evaporator Tube Leakage Estimation in Supercharged Boiler by Yulong Xue, Dongliang Li, Yu Song, Shaojun Xia, Jingxing Wu

“…To address these issues, this study proposes a novel deep learning framework (LSTM-CNN–attention), combining a Long Short-Term Memory (LSTM) network with a dual-pathway spatial feature extraction structure (ACNN) that includes an attention mechanism(attention) and a 1D convolutional neural network (1D-CNN) parallel pathway. …”
Get full text

Dynamic atrous attention and dual branch context fusion for cross scale Building segmentation in high resolution remote sensing imagery by Yaohui Liu, Shuzhe Zhang, Xinkai Wang, Rui Zhai, Hu Jiang, Lingjia Kong

“…Among them, we introduced the Shift Operation module and the Self-Attention module, which adopt a dual-branch structure to respectively capture local spatial dependencies and global correlations, and perform weight coupling to achieve highly complementary contextual information fusion. …”
Get full text

Rice Leaf Disease Image Enhancement Based on Improved CycleGAN by YAN Congkuan, ZHU Dequan, MENG Fankai, YANG Yuqing, TANG Qixing, ZHANG Aifang, LIAO Juan

“…These included user perception evaluation (UPE), structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), and the performance of disease recognition within object detection frameworks. …”
Get full text

FPA-based weighted average ensemble of deep learning models for classification of lung cancer using CT scan images by Liang Zhou, Achin Jain, Arun Kumar Dubey, Sunil K. Singh, Neha Gupta, Arvind Panwar, Sudhakar Kumar, Turki A. Althaqafi, Varsha Arya, Wadee Alhalabi, Brij B. Gupta

“…Abstract Cancer is among the most dangerous diseases contributing to rising global mortality rates. Lung cancer, particularly adenocarcinoma, is one of the deadliest forms and severely impacts human life. …”
Get full text

A low illumination target detection method based on a dynamic gradient gain allocation strategy by Zhiqiang Li, Jian Xiang, Jiawen Duan

“…Firstly, efficient multi-scale feature fusion is performed by using a new neck structure in the original model so that it can fully exchange high-level semantic information and low-level spatial information. …”
Get full text

MultiRepPI: a cross-modal feature fusion-based multiple characterization framework for plant peptide-protein interaction prediction by Yu Zhiguo, Li Zixuan, Li Peng

“…First, most methods fail to adequately integrate multimodal information such as sequence, structure, and disorder properties, leading to inadequate characterization of complex interaction patterns. …”
Get full text