Deep learning based identification of rock minerals from un-processed digital microscopic images of undisturbed broken-surfaces by M.A. Dalhat, Sami A. Osman

“…This study employed convolutional neural networks (CNNs) for the classification of rock minerals based on 3179 RGB-scale original microstructural images of undisturbed broken surfaces. …”
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An imaging and genetic-based deep learning network for Alzheimer's disease diagnosis by Yuhan Li, Donghao Niu, Keying Qi, Dong Liang, Dong Liang, Xiaojing Long, Xiaojing Long

“…Our model leveraged a convolutional neural network (CNN) to extract whole-brain structural features, a Transformer network to capture genetic features, and employed a cross-transformer-based network for comprehensive feature fusion. …”
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Automating field‐based floral surveys with machine learning by Nicholas Sookhan, Shane Sookhan, Devlin Grewal, J. Scott MacIvor

“…Aerial photography was collected across 10 sites located in and around Rouge National Urban Park, Toronto, Canada using a consumer‐grade drone. A convolutional neural network (CNN) was trained to semantically segment, or identify and categorize, pixel clusters which represent flowers in the collected aerial imagery. …”
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Explainable brain age prediction: a comparative evaluation of morphometric and deep learning pipelines by Maria Luigia Natalia De Bonis, Giuseppe Fasano, Angela Lombardi, Carmelo Ardito, Antonio Ferrara, Eugenio Di Sciascio, Tommaso Di Noia

“…In this study, we present a comparative evaluation of two pipelines: one using morphometric features from FreeSurfer and the other employing 3D convolutional neural networks (CNNs). Using a multisite neuroimaging dataset, we assessed both model performance and the interpretability of predictions through eXplainable Artificial Intelligence (XAI) methods, applying SHAP to the feature-based pipeline and Grad-CAM and DeepSHAP to the CNN-based pipeline. …”
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Deep Learning-Based Fully Automatic Segmentation of the Paranasal Sinuses in Chronic Rhinosinusitis Patients Using Computed Tomographic Images by Yuhang Wang, Xiaolei Zhang, Weidong Du, Na Dai, Yi Lyv, Keying Wu, Yiyang Tian, Yuxin Jie, Yu Lin, Weipiao Kang

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Robustness of the RGB image-based estimation for rice above-ground biomass by utilizing the dataset collected across multiple locations by Kota Nakajima, Kazuki Saito, Yasuhiro Tsujimoto, Toshiyuki Takai, Atsushi Mochizuki, Tomoaki Yamaguchi, Ali Ibrahim, Salifou Goube Mairoua, Bruce Haja Andrianary, Keisuke Katsura, Yu Tanaka

“…This study aims to assess the robustness of a convolutional neural network (CNN) model for rice AGB estimation across five locations in three countries, and to demonstrate the feasibility of robust model via a practical approach. …”
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MultiModal Ensemble Approach Leveraging Spatial, Skeletal, and Edge Features for Enhanced Bangla Sign Language Recognition by Khan Abrar Shams, Md. Rafid Reaz, Mohammad Ryan Ur Rafi, Sanjida Islam, Md. Shahriar Rahman, Rafeed Rahman, Md. Tanzim Reza, Mohammad Zavid Parvez, Subrata Chakraborty, Biswajeet Pradhan, Abdullah Alamri

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A Closed-loop Detection Algorithm Based on Dynamic Time Warping by ZHU Tian, PENG Zhichuan, ZHANG Zhiteng, ZHU Zemin, XIE Yongbo, WANG Wenming

“…At the same time, it uses convolutional neural network to extract image features and the results are more advanced and abstract, and this enhances the robustness of the algorithm. …”
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Some issues of multi-criteria optimization of parameters of complex systems by R. V. Guseynov, M. R. Guseynova, K. A. Alieva

“…The study was carried out on the basis of multicriteria optimization methods, the hierarchy analysis method, the convolution method, and heuristic methods.Result. The paper describes general problems of multicriteria optimization of mechanical systems. …”
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Prediction and classification of wheat plant disease in Pakistan using deep learning techniques by Muhammad Usman Malik, Muhammad Faisal Hayat

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Calculus accumulation-based method for extracting values of instrumentation image by Dianming Wang, Li Zhou, Xiangxin Chen, Mingxin Yi, Xiaoju Yin

“…A double-pointer meter reading recognition scheme based on two-dimensional convolution and calculus accumulation is proposed. The weighted multifeature matching algorithm is used to accurately obtain the center coordinates of the rotating shaft to improve the success rate of meter image recognition. …”
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Ground Fissure Identification in Mining Areas from UAV Images Based on DN-CAMSCBNet by Haibin Hu, Xinhui Guo, Jie Xiao

“…Meanwhile, it introduces the multiscale convolution block and Nesterov-accelerated adaptive moment estimation. …”
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Traction Drive Control System for Railway Electric Rolling Stock Based on the Application of Power Factor as an Optimization Criterion by Goolak S., Gorobchenko O., Holub H., Kulbovskiy I., Petrychenko O.

“…The stated objective has been achieved through the solution of the following tasks: development of an algorithm for applying traction drive power factor as an optimization criterion, taking into account stochastic disturbance effects acting on the traction drive from the traction power supply system and mechanical load; development of a structural scheme for an optimized automatic control system of electric rolling stock traction drives, in which the proposed algorithm is implemented. The most important results are: the obtained analytical time dependency of the traction drive power factor, representing a convolution of two-time functions—efficiency and active power utilization coefficient of the traction drive—and the developed algorithm for eliminating stochastic disturbance effects acting on the traction drive from the traction power supply system and mechanical load. …”
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Deep CNN ResNet-18 based model with attention and transfer learning for Alzheimer's disease detection by Sofia Biju Francis, Sofia Biju Francis, Jai Prakash Verma

“…Alzheimer's disease leads to a rapid and irreversible decline in cognitive abilities by damaging memory cells.MethodsA ResNet-18-based system is proposed, integrating Depth Convolution with a Squeeze and Excitation (SE) block to minimize tuning parameters. …”
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DSNET: A Lightweight Segmentation Model for Segmentation of Skin Cancer Lesion Regions by Yucong Chen, Guang Yang, Xiaohua Dong, Junying Zeng, Chuanbo Qin

“…Currently, most skin disease segmentation tasks tend to use large models to achieve better segmentation performance. …”
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A Systematic Survey of AI Models in Financial Market Forecasting for Profitability Analysis by Bilal Hassan Ahmed Khattak, Imran Shafi, Abdul Saboor Khan, Emmanuel Soriano Flores, Roberto Garcia Lara, Md. Abdus Samad, Imran Ashraf

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Intercomparison of Machine Learning Models for Spatial Downscaling of Daily Mean Temperature in Complex Terrain by Sudheer Bhakare, Sara Dal Gesso, Marco Venturini, Dino Zardi, Laura Trentini, Michael Matiu, Marcello Petitta

“…We compare three machine learning models—artificial neural network (ANN), random forest (RF), and convolutional neural network (CNN)—for spatial downscaling of temperature at 2 m above ground (T2M) from a 9 km ERA5-Land reanalysis to 1 km in a complex terrain area, including the Non Valley and the Adige Valley in the Italian Alps. …”
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A Comparative Analysis of Deep Learning-Based Segmentation Techniques for Terrain Classification in Aerial Imagery by Martina Formichini, Carlo Alberto Avizzano

“…Background: Deep convolutional neural networks (CNNs) have become widely popular for many imaging applications, and they have also been applied in various studies for monitoring and mapping areas of land. …”
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MoAGL-SA: a multi-omics adaptive integration method with graph learning and self attention for cancer subtype classification by Lei Cheng, Qian Huang, Zhengqun Zhu, Yanan Li, Shuguang Ge, Longzhen Zhang, Ping Gong

“…Next, three-layer graph convolutional networks are employed to extract omic-specific graph embeddings. …”
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An air target intention data extension and recognition model based on deep learning by Bo Cao, Qinghua Xing, Longyue Li, Weijie Lin

“…Finally, the temporal block based on dilated causal convolution is built to solve the problem of temporal feature extraction. …”
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