Enhanced YOLOv8-based pavement crack detection: A high-precision approach. by ZuXuan Zhang, HongLi Zhang, TongJia Zhang

“…Firstly, this paper introduces deep separable Convolution (DWConv) into YOLOv8 backbone network to capture crack information more flexibly and improve the recognition accuracy of the model. …”
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Hyperspectral target detection based on graph sampling and aggregation network. by Tie Li, Hongfeng Jin, Zhiqiu Li

“…Concurrently, it exhibits a remarkable adaptability to the diverse characteristics of different datasets, thus validating its high level of accuracy and robustness.…”
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Logatome and Sentence Recognition Related to Acoustic Parameters of Enclosures by Jedrzej KOCIŃSKI, Edward OZIMEK

“…Six enclosures were chosen: a church, an assembly hall of a music school, two courtrooms of different volumes, a typical auditorium and a university concert hall. …”
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A YOLOv8 algorithm for safety helmet wearing detection in complex environment by Chunning Song, Yinzhong Li

“…Finally, propose a new structure of information aggregation, It better fuses information about target characteristics and context at different scales, allowing the information to flow between channels, thus improving the algorithm’s performance. …”
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An Efficient Recommendation Algorithm Based on Heterogeneous Information Network by Ying Yin, Wanning Zheng

“…Heterogeneous information networks can naturally simulate complex objects, and they can enrich recommendation systems according to the connections between different types of objects. At present, a large number of recommendation algorithms based on heterogeneous information networks have been proposed. …”
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Image semantic segmentation with hierarchical feature fusion based on deep neural network by Dawei Yang, Yan Du, Hongli Yao, Liyan Bao

“…Deep neural network can not effectively use the feature information between different levels. The accuracy of image semantic segmentation is damaged. …”
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High-resolution population mapping by fusing remote sensing and social sensing data considering the spatial scale mismatch issue by Peijun Feng, Zheng Ma, Jining Yan, Leigang Sun, Nan Wu, Luxiao Cheng, Dongmei Yan

“…However, the significant scale difference between the regional and grid levels, combined with the simple integration of multi-source data features without considering the spatial dependence of the population, results in lower accuracy. …”
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Enhanced Rolling Bearing Fault Diagnosis Using Multimodal Deep Learning and Singular Spectrum Analysis by Yunhang Wang, Hongwei Wang, Ruoyang Bai, Yuxin Shi, Xicong Chen, Qingang Xu

“…Based on this, a recursive gated convolutional neural network (RGCNN) is designed to process the STFT image data, while a 1D convolutional neural network (1DCNN) is specifically optimized for training with time series data. …”
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Simulation and Recognition of Concrete Lining Infiltration Degree via an Indoor Experiment by Dongsheng Wang, Jun Feng, Xinpeng Zhao, Yeping Bai, Yujie Wang, Xuezeng Liu

“…To solve this problem, we propose a recognition method by using a deep convolutional neural network. We carry out laboratory tests, prepare cement mortar specimens with different saturation levels, simulate different degrees of infiltration of tunnel concrete linings, and establish an infrared thermal image data set with different degrees of infiltration. …”
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Combining Region-Guided Attention and Attribute Prediction for Thangka Image Captioning Method by Fujun Zhang, Wendong Kang, Wenjin Hu

“…This predictor leverages feature maps from four different convolutional blocks within the region-guided module to incorporate more detailed information into the model. …”
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Medical Image Hybrid Watermark Algorithm Based on Frequency Domain Processing and Inception v3 by Yu Fan, Jingbing Li, Uzair Aslam Bhatti, Saqib Ali Nawaz, Yenwei Chen

“…Existing research has mostly focused on optimizing individual techniques, lacking comprehensive solutions that integrate the strengths of different methods. This article proposes a hybrid digital watermarking algorithm for medical images based on frequency domain transformation and deep learning convolutional neural networks. …”
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A hybrid bio-inspired augmented with hyper-parameter deep learning model for brain tumor classification by Morolake Oladayo Lawrence

“…The CNN model is adjusted for different convolutional layers and fully connected layers to identify patterns and features in brain tumor pictures using an enhanced salp swarm algorithm (SSA) with kernel extreme learning machine (KELM). …”
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Inference of Gene Regulatory Networks for Breast Cancer Based on Genetic Modules by Yihao Chen, Ling Guo, Yue Pan, Hui Cai, Zhitong Bing

“…This new method combining genetic modules and convolutional neural networks is presented to infer GRNs from the RNA sequencing data of breast cancer. …”
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Predicting road quality using high resolution satellite imagery: A transfer learning approach. by Ethan Brewer, Jason Lin, Peter Kemper, John Hennin, Dan Runfola

“…We test and compare eight different convolutional neural network architectures using a dataset of 53,686 images of 2,400 kilometers of roads in the United States, in which each road segment is measured as "low", "middle", or "high" quality using an open, cellphone-based measuring platform. …”
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Deep Learning Forecasting Model for Market Demand of Electric Vehicles by Ahmed Ihsan Simsek, Erdinç Koç, Beste Desticioglu Tasdemir, Ahmet Aksöz, Muammer Turkoglu, Abdulkadir Sengur

“…This model, called EVs-PredNet, is developed using deep learning methods such as LSTM (Long Short-Term Memory) and CNNs (Convolutional Neural Networks). The model comprises convolutional, activation function, max pooling, LSTM, and dense layers. …”
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Cross modal recipe retrieval with fine grained modal interaction by Fan Zhao, Yuqing Lu, Zhuo Yao, Fangying Qu

“…Preceding a hierarchical recipe Transformer for encoding individual recipe components, we introduce the cross-component multiscale recipe enriching (CCMRE) module, which enhances the components of the recipe through fully convolutional operations with convolutional kernels of different lengths. …”
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YOLO-GML: An object edge enhancement detection model for UAV aerial images in complex environments. by Zhihao Zheng, Jianguang Zhao, Jingjing Fan

“…Finally, we propose a Lightweight layered Shared Convolutional BN(LLSCB) Detection Head based on LSCD, so that the detection heads share the convolutional layer, and the BN is calculated independently, which improves the detection accuracy and reduces the number of parameters. …”
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HUMAN EMOTION RECOGNITION SYSTEM USING DEEP LEARNING ALGORITHMS by Kateryna Yuvchenko, Valentyn Yesilevskyi, Olena Sereda

“…They can be expressed in different ways: facial expressions, posture, motor reactions, voice. …”
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EAD-YOLOv10: Lightweight Steel Surface Defect Detection Algorithm Research Based on YOLOv10 Improvement by Hu Haoyan, Tong Jinwu, Wang Haibin, Lu Xinyun

“…Finally, the designed C2f_EMSCP method is integrated into the backbone and neck networks, effectively merging multi-scale convolutional networks and position-aware modules to enhance the model’s sensitivity and detection capability for multi-scale targets by fusing feature maps of different scales. …”
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Automatic Quantification of Atmospheric Turbulence Intensity in Space-Time Domain by Damián Gulich, Myrian Tebaldi, Daniel Sierra-Sosa

“…These representations are then fed into a Convolutional Neural Network for classification. This network effectively learns to discriminate between different turbulence regimes based on the spatio-temporal features extracted from a real-world experiment captured in video slices.…”
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