Analysis of the criteria selection problem in diversification models by Анна Бакурова, Алла Савранська, Еліна Терещенко, Дмитро Широкорад, Марк Шевчук

“… The digitalization of the economy reduces the cost of doing business by automating the relevant processes, but any transformation creates new risks and economic instability. …”
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Analysis of the criteria selection problem in diversification models by Анна Бакурова, Алла Савранська, Еліна Терещенко, Дмитро Широкорад, Марк Шевчук

“… The digitalization of the economy reduces the cost of doing business by automating the relevant processes, but any transformation creates new risks and economic instability. …”
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Analysis of the criteria selection problem in diversification models by Анна Бакурова, Алла Савранська, Еліна Терещенко, Дмитро Широкорад, Марк Шевчук

“… The digitalization of the economy reduces the cost of doing business by automating the relevant processes, but any transformation creates new risks and economic instability. …”
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YOLO-RD: A Road Damage Detection Method for Effective Pavement Maintenance by Wei Wang, Xiaoru Yu, Bin Jing, Ziqi Tang, Wei Zhang, Shengyu Wang, Yao Xiao, Shu Li, Liping Yang

“…Road damage detection is crucial for ensuring road safety and minimizing maintenance costs. However, detecting small damage, managing complex backgrounds, and identifying irregular damage shapes remain significant challenges. …”
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A Dense Pyramidal Residual Network with a Tandem Spectral–Spatial Attention Mechanism for Hyperspectral Image Classification by Yunlan Guan, Zixuan Li, Nan Wang

“…In recent years, convolutional neural networks (CNNs) have become a potent tool for hyperspectral image classification (HSIC), where classification accuracy, computational cost, and generalization ability are the main focuses. …”
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High-Precision and Low-Complexity Silicon Waveguide-Integrated Temperature Sensor System by Zhiming Zhang, Haole Kong, Yi Li

“…The waveguide layout is optimized through the finite-difference time-domain (FDTD) simulations, and a compressed taper structure improves the efficiency of speckle data collection while reducing the system complexity and cost. To achieve precise temperature demodulation, this paper employed a convolutional neural network (CNN) for nonlinear fitting. …”
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Quantization-Aware Training With Dynamic and Static Pruning by Sangho An, Jongyun Shin, Jangho Kim

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Simplified LSL-Net Architecture for Unmanned Aerial Vehicle Detection in Real-Time by Francisco David Camacho-Gonzalez, Nestor Andres Garcia-Rojas, José Francisco Martínez-Trinidad, Jesús Ariel Carrasco-Ochoa

“…We introduce a simplified LSL-Net architecture using dilated convolutions to achieve a lower-cost architecture with good detection capabilities. …”
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Prune and Distill: A Novel Knowledge Distillation Method for GCNs-Based Recommender Systems by Peng Yi, Zhaoxian Li, Lu Chen, Cheng Yang, Xiongcai Cai

“…Graph convolutional networks (GCNs)-based recommenders have demonstrated remarkable recommendation performances but suffer from prohibitive computational cost, limiting their practical deployment. …”
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Advanced Diabetic Retinopathy Detection with the R–CNN: A Unified Visual Health Solution by Sravya Valluri Sri, Srinivasu Parvathaneni Naga, Shafi Jana, Hołubowski Waldemar, Zielonka Adam

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A 3D lightweight network with Roberts edge enhancement model (LR-Net) for brain tumor segmentation by Qingxu Meng, Weijiang Wang, Hang Qi, Hua Dang, Minli Jia, Xiaohua Wang

“…We propose a 3D Spatial Shift Convolution and Pixel Shuffle (SSCPS) module, the SSCPS module present a low-parameter, low-computational-cost spatial shift convolution that overcomes the limitation of receptive field and improves the ability to extract global contextual information, Pixel Shuffle (PS) module extracts spatial information from feature dimensions, efficiently replacing traditional upsampling module. …”
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Noise2Variance: Dual networks with variance constraint for self‐supervised real‐world image denoising by Hanlin Tan, Yu Liu, Maojun Zhang

“…Traditional methods utilizing convolutional neural networks (CNN) for denoising are trained using pairs of noisy and clean images to comprehend the transformation from a noisy image to a clean one. …”
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TSD-Net: A Traffic Sign Detection Network Addressing Insufficient Perception Resolution and Complex Background by Chengcheng Ma, Chang Liu, Litao Deng, Pengfei Xu

“…Existing methods face limitations including high computational cost, inconsistent feature alignment, and insufficient resolution in detection heads. …”
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DEMNet: A Small Object Detection Method for Tea Leaf Blight in Slightly Blurry UAV Remote Sensing Images by Yating Gu, Yuxin Jing, Hao-Dong Li, Juntao Shi, Haifeng Lin

“…An efficient EMAFPN neck structure further facilitates deep–shallow feature interaction while reducing the computational cost. Additionally, a novel CMLAB module replaces the traditional C2f structure, employing multi-scale convolutions and local attention mechanisms to recover semantic information in blurry regions and better detect densely distributed small targets. …”
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Improved YOLOv8-Based Algorithm for Citrus Leaf Disease Detection by Zhengbing Zheng, Yibang Zhang, Luchao Sun

“…This modification increases the model’s parameter count without adding to the computational cost in terms of floating-point operations. Next, a fast convolution layer is implemented to replace the original C2f module, improving both detection accuracy and computational efficiency. …”
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SLiTRANet: An EEG-Based Automated Diagnosis Framework for Major Depressive Disorder Monitoring Using a Novel LGCN and Transformer-Based Hybrid Deep Learning Approach by Sagnik de, Anurag Singh, Vivek Tiwari, Harshita Patel, G. N. Vivekananda, Dharmendra Singh Rajput

“…Due to advancements in sensor technology, fast, convenient, and cost-effective EEG acquisition is now possible, resulting in many EEG-based healthcare monitoring applications in recent years. …”
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BSO-CNN: A BSO Pressure Optimized CNN Model for Water Distribution Networks by Waghmare Shwetambari Pandurang, Renu Praveen Pathak, Imtiyaz Ahmad Wani

“…To overcome these difficulties, a brand-new Convolutional Neural Network (CNN) Pressure Optimization Model is proposed. …”
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Learnable Resized and Laplacian-Filtered U-Net: Better Road Marking Extraction and Classification on Sparse-Point-Cloud-Derived Imagery by Miguel Luis Rivera Lagahit, Xin Liu, Haoyi Xiu, Taehoon Kim, Kyoung-Sook Kim, Masashi Matsuoka

“…While cost effective, these sensors produce sparser point clouds, leading to poor feature representation and degraded performance in deep learning techniques, such as convolutional neural networks (CNN), for tasks like road marking extraction and classification, which are essential for HD map generation. …”
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EA-CNN: Enhanced attention-CNN with explainable AI for fruit and vegetable classification by Zeshan Aslam Khan, Muhammad Waqar, Khalid Mehmood Cheema, Ali Abu Bakar Mahmood, Quratul Ain, Naveed Ishtiaq Chaudhary, Abdullah Alshehri, Sultan S. Alshamrani, Muhammad Asif Zahoor Raja

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LST-BEV: Generating a Long-Term Spatial–Temporal Bird’s-Eye-View Feature for Multi-View 3D Object Detection by Qijun Feng, Chunyang Zhao, Pengfei Liu, Zhichao Zhang, Yue Jin, Wanglin Tian

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