Artificial intelligence in acoustic ecology: Soundscape classification in the Cerrado by Bruno Daleffi da Silva, Linilson Rodrigues Padovese

“…The performance comparison of these models revealed the superiority of the Convolutional Neural Network (CNN), which, although requiring higher computational costs and training time, provided high accuracy in classifications and valuable insights through the application of the LIME explainability technique. …”
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CLSTM-MT (a Combination of 2-Conv CNN and BiLSTM Under the Mean Teacher Collaborative Learning Framework): Encryption Traffic Classification Based on CLSTM (a Combination of 2-Conv... by Xiaozong Qiu, Guohua Yan, Lihua Yin

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Automatic Number Plate Detection and Recognition System for Small-Sized Number Plates of Category L-Vehicles for Remote Emission Sensing Applications by Hafiz Hashim Imtiaz, Paul Schaffer, Paul Hesse, Martin Kupper, Alexander Bergmann

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An Empirical Model-Based Algorithm for Removing Motion-Caused Artifacts in Motor Imagery EEG Data for Classification Using an Optimized CNN Model by Rajesh Kannan Megalingam, Kariparambil Sudheesh Sankardas, Sakthiprasad Kuttankulangara Manoharan

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Artificial Intelligence in Cardiovascular Diagnosis: Innovations and Impact on Disease Screenings by Amber Ahmad, Sahil Ahmad, Rida Ahmad, Jahnavi Bodi, Abdulla Mohamed, Ahmad Wasim

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AI-driven demand forecasting for enhanced energy management in renewable microgrids: A hybrid LSTM-CNN approach by Bashiru olalekan ariyo, mutalub adesina lambe, olalekan ogunbiyi, musa abdulwaheed, bilkisu jimada ojuolape, monsurat omolara balogun

“…Methods: A hybrid forecasting model that combines long short-term memory (LSTM) networks and Convolutional Neural Networks (CNN) was proposed. The model leverages historical energy consumption and meteorological data for training, ensuring robust and accurate predictions. …”
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Predicting water-based drilling fluid filtrate volume in close to real time from routine fluid property measurements by Shadfar Davoodi, Mohammed Ba Geri, David A. Wood, Mohammed Al-Shargabi, Mohammad Mehrad, Alireza Soleimanian

“…Drilling operations depend on precisely controlling drilling fluid filtration volume (FV), which affects formation integrity, costs, and borehole stability. Maintaining optimal FV is essential to prevent well control issues, yet forecasting it is challenging due to process complexity and measurement limitations. …”
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Short-term Wind Power Forecasting Based on BWO‒VMD and TCN‒BiGRU by LU Jing, ZHANG Yanru, WANG Rui

“…Short-term wind power forecasting helps improve grid stability, optimize wind farm power generation plans, and reduce operating costs, enhancing the economic benefits of wind power and supporting the goals of low-carbon development. …”
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A Short-Term Carbon Emission Accounting Method for Power Industry Using Electricity Data Based on a Combined Model of CNN and LightGBM by ZENG Jincan, HE Gengsheng, LI Yaowang, DU Ershun, ZHANG Ning, ZHU Haojun

“…This method utilizes convolutional neural networks (CNNs) for feature extraction, and light gradient boosting machine (LightGBM) for carbon emission estimation based on extracted features. …”
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RMDNet: RNA-aware dung beetle optimization-based multi-branch integration network for RNA–protein binding sites prediction by Jiangbo Zhang, Yunhui Peng, Feifei Cui, Zilong Zhang, Shankai Yan, Qingchen Zhang

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Models, systems, networks in economics, engineering, nature and society by D.V. Mirosh

“…The use of the developed neural networks allows to improve diagnostic studies for asynchronous machines of various capacities, easily adapt them to different dimensional designs, improve the quality of diagnostic services provided and reduce the labor costs of diagnostic specialists in the study of the parameters of the state of an electric machine.…”

Semantic Segmentation of Archaeological Features on Public Lands: Case Study of Historical Cotton Terraces within the Piedmont National Wildlife Refuge, Georgia, USA by Claudine Gravel-Miguel, Grant Snitker, Jayde N. Hirniak, Katherine Peck, Alex Fetterhoff

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QoS Routing in Telecommunications Networks by N. I. Listopad, O. A. Lavshuk

“…The results of numerical modeling of the search for the optimal path for various values of weight coefficients and cost coefficients are presented. It is shown that when choosing a path for multi-criteria optimization, it is necessary to choose the coefficients of the additive convolution as the product of the weight coefficients and the cost coefficients directly. …”
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PO-YOLOv5: A defect detection model for solenoid connector based on YOLOv5. by Ming Chen, Yuqing Liu, Xing Wei, Zichen Zhang, Oleg Gaidai, Hengshou Sui, Bin Li

“…Replacing conventional convolution with dynamic convolution enhances the detection accuracy of the model and reduces the inference time. …”
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A Lightweight Person Detector for Surveillance Footage Based on YOLOv8n by Qicheng Wang, Guoqiang Feng, Zongzhe Li

“…Next, a heterogeneous PAFPN with improved MSBlock was formed using heterogeneous convolution kernels. Finally, AKConv, a variable kernel convolution, was applied to further reduce the number of parameters and the computational cost while improving accuracy. …”
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Optimized YOLOv8 framework for intelligent rockfall detection on mountain roads by Peng Peng, Langchao Gao, Jiachun Li, Hongzhen Zhang

“…The algorithm enhances detection performance through the following optimizations: (1) integrating a lightweight DeepLabv3+ road segmentation module at the input stage to generate mask images, which effectively exclude non-road regions from interference; (2) replacing Conv convolution units in the backbone network with Ghost convolution units, significantly reducing model parameters and computational cost while improving inference speed; (3) introducing the CPCA (Channel Priori Convolution Attention) mechanism to strengthen the feature extraction capability for targets with diverse shapes; and (4) incorporating skip connections and weighted fusion in the Neck feature extraction network to enhance multi-scale object detection. …”
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A Lightweight Semantic- and Graph-Guided Network for Advanced Optical Remote Sensing Image Salient Object Detection by Jie Liu, Jinpeng He, Huaixin Chen, Ruoyu Yang, Ying Huang

“…This module incorporates non-local operations under graph convolution domain to deeply explore high-order relationships between adjacent layers, while utilizing depth-wise separable convolution blocks to significantly reduce computational cost. …”
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A small underwater object detection model with enhanced feature extraction and fusion by Tao Li, Yijin Gang, Sumin Li, Yizi Shang

“…Next, a variable kernel convolution (VKConv) is proposed to dynamically adjust the convolution kernel size, enabling better multi-scale feature extraction. …”
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YOLOLS: A Lightweight and High-Precision Power Insulator Defect Detection Network for Real-Time Edge Deployment by Qinglong Wang, Zhengyu Hu, Entuo Li, Guyu Wu, Wengang Yang, Yunjian Hu, Wen Peng, Jie Sun

“…To further optimize performance, a lightweight shared-convolution detection head significantly reduces parameter count and computational cost without compromising detection accuracy. …”
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L-ENet: An Ultralightweight SAR Image Detection Network by Yutong Wang, Min Miao, Shiliang Zhu

“…Experimental results show that L-ENet has a computational cost of 0.6 M and a parameter count of 2.1 giga floating point operations per second. …”
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