Integrating Viewing Direction and Image Features for Robust Multi-View Multi-Object 3D Pedestrian Tracking by R. Ali, M. Mehltretter, C. Heipke

Get full text

A dual encoder network with multiscale feature fusion and multiple pooling channel spatial attention for skin scar image segmentation by Weiyuan Yang, Xiaolin Wang, Guangwei Chen, Jianming Wen, Dexing Kong, Jianfeng Zhang, Xinyang Ge, Hao Xu, Jianhua Qin

Get full text

Triple-Stream Deep Feature Selection with Metaheuristic Optimization and Machine Learning for Multi-Stage Hypertensive Retinopathy Diagnosis by Süleyman Burçin Şüyun, Mustafa Yurdakul, Şakir Taşdemir, Serkan Biliş

“…In the first stage, 14 well-known Convolutional Neural Network (CNN) models were evaluated, and the top three models were identified. …”
Get full text

Research on Chinese Semantic Relation Extraction in Marine Engine Rooms Based on Multi-Feature Fusion by Xicai Liu, Zhengquan Wang, Fubo Wang

“…To incorporate syntactic graph structural features, we process this matrix and BERT-encoded embeddings using a graph convolutional neural network (GCN). …”
Get full text

UGC-Net: Uncertainty-Guided Cost Volume Optimization with Contextual Features for Satellite Stereo Matching by Wonje Jeong, Soon-Yong Park

Get full text

Fine-grained crop pest classification based on multi-scale feature fusion and mixed attention mechanisms by Yiheng Qian, Zhiyong Xiao, Zhaohong Deng

“…Additionally, a Transformer block is integrated to overcome the limitations of traditional convolutional approaches in capturing global contextual information. …”
Get full text

Lumbar and pelvic CT image segmentation based on cross-scale feature fusion and linear self-attention mechanism by Chaofan Li, Liping Chen, Qiong Liu, Jinnan Teng

Get full text

TFTformer: A novel transformer based model for short-term load forecasting by Ahmad Ahmad, Xun Xiao, Huadong Mo, Daoyi Dong

“…Additionally, a Temporal Convolutional Network is integrated within the Transformer’s encoder, employing causal convolutions and dilation to adapt to the sequential nature of data with an expanded receptive field. …”
Get full text

A Blueberry Maturity Detection Method Integrating Attention-Driven Multi-Scale Feature Interaction and Dynamic Upsampling by Haohai You, Zhiyi Li, Zhanchen Wei, Lijuan Zhang, Xinhua Bi, Chunguang Bi, Xuefang Li, Yunpeng Duan

“…Additionally, the neck integrates a dynamic sampling technique, replacing traditional upsampling methods, allowing for more precise feature integration during feature transfer from P5 to P4 and P4 to P3. …”
Get full text

MambaCAttnGCN+: a comprehensive framework integrating MambaTextCNN, cross-attention and graph convolution network for piRNA-disease association prediction by Dengju Yao, Xiangkui Li, Xiaojuan Zhan, Bo Zhang, Jian Zhang

“…A heterogeneous graph convolution method was then applied to identify potential associations between piRNAs and diseases, with cross-attention mechanisms further enhancing node features. …”
Get full text

A Novel 3D Convolutional Neural Network-Based Deep Learning Model for Spatiotemporal Feature Mapping for Video Analysis: Feasibility Study for Gastrointestinal Endoscopic Video Cla... by Mrinal Kanti Dhar, Mou Deb, Poonguzhali Elangovan, Keerthy Gopalakrishnan, Divyanshi Sood, Avneet Kaur, Charmy Parikh, Swetha Rapolu, Gianeshwaree Alias Rachna Panjwani, Rabiah Aslam Ansari, Naghmeh Asadimanesh, Shiva Sankari Karuppiah, Scott A. Helgeson, Venkata S. Akshintala, Shivaram P. Arunachalam

“…To reduce computational complexity, a (2 + 1)D convolution is used in place of full 3D convolution. …”
Get full text

FEPA-Net: A Building Extraction Network Based on Fusing the Feature Extraction and Position Attention Module by Yuexin Liu, Yulin Duan, Xuya Zhang, Wen Zhang, Chang Wang

“…Firstly, the number of convolutional operations in the model was increased to extract more abstract features of the objects on the ground; secondly, within the network, the ordinary convolution is substituted with the dilated convolution. …”
Get full text

Integrating attention mechanism and boundary detection for building segmentation from remote sensing images by Ping Liu, Yu Gao, Xiangtian Zheng, Hesong Wang, Yimeng Zhao, Xinru Wu, Zehao Lu, Zhichuan Yue, Yuting Xie, Shufeng Hao

“…We propose a building semantic segmentation method to improve the traditional Unet convolutional neural network by integrating attention mechanism and boundary detection. …”
Get full text

Integration of wing pattern morphology and deep learning to support Plusiinae (Lepidoptera: Noctuidae) pest identification by Karina M. Torres, Chenjiao Tan, Kayla A. Mollet, Allan H. Smith-Pardo, Rui Xu, Changying Li, Silvana V. Paula-Moraes

Get full text

Predicting Index Trend Using Hybrid Neural Networks with a Focus on Multi-Scale Temporal Feature Extraction in the Tehran Stock Exchange by Mohammad Osoolian, Ali Nikmaram, Mahdi Karimi

“…MethodsThe hybrid neural network architecture that has been put forward integrates the unique capabilities of convolutional neural networks (CNNs) in the realm of feature extraction with the effectiveness of long short-term memory (LSTM) networks in capturing temporal dependencies. …”
Get full text

A human activity recognition model based on deep neural network integrating attention mechanism by Feng Xu, Xuchen Gao, Weigang Wang

Get full text

Identification of rice leaf disease based on DepMulti-Net by Kui Hu, Kui Hu, Xinying Zheng, Xinying Zheng, Xinyao Su, Lei Wu, Yongmin Liu, Yongmin Liu, Zhenhua Deng

“…Moreover, the integration of the feature reuse mechanism and inverse bottleneck structure further improved the model’s recognition accuracy for fine-grained disease features. …”
Get full text

GM2FFNet: Grouped Multiscale Multiangle Feature Fusion Network With Center Attention for Hyperspectral Image Classification by Junding Sun, Haoxiang Dong, Yanlong Gao, Xiaosheng Wu, Jianlong Wang, Yudong Zhang

“…Second, a grouped multiangle convolution module extracts features from multiple directions, with an adaptive fusion module further integrating this information. …”
Get full text

MSBiLSTM-Attention: EEG Emotion Recognition Model Based on Spatiotemporal Feature Fusion by Yahong Ma, Zhentao Huang, Yuyao Yang, Zuowen Chen, Qi Dong, Shanwen Zhang, Yuan Li

“…This paper introduces a novel deep learning technique that integrates multi-scale convolution and bidirectional long short-term memory networks with an attention mechanism for automatic EEG feature extraction and classification. …”
Get full text

EEG-Based Seizure Detection Using Dual-Branch CNN-ViT Network Integrating Phase and Power Spectrograms by Zhuohan Wang, Yaoqi Hu, Qingyue Xin, Guanghao Jin, Yazhou Zhao, Weidong Zhou, Guoyang Liu

Get full text