Measuring the Company’s Capabilities and Assessing their Impact on Its Economic Results: Analytic Tools by E. P. Tretiakova, M. S. Tretiakova

“…To solve analytical tasks at different levels of management, combinations of methods, tools and indicators called “research formats” (detailed, diagnostic, express diagnostic analysis) were developed. …”
Get full text

CSCA-YOLOv8: A lightweight network model for evaluating drought resistance in mung bean. by Dongshan Jiang, Jinyang Liu, Haomiao Zhang, Wenxiang Liang, Ziqiu Luo, Wenlong An, Shicong Li, Xin Chen, Xingxing Yuan, Shangbing Gao

“…In the actual data analysis, we used the collected 4808 chlorophyll fluorescence images of the natural mung bean population under drought stress to make the Mungbean Drought Datatset(MDD) and made classification labels for each image according to different drought resistance levels, which were 0, 1, 2, 3, 4 and 5. …”
Get full text

ALPD-Net: a wild licorice detection network based on UAV imagery by Jing Yang, Huaibin Qin, Jianguo Dai, Guoshun Zhang, Miaomiao Xu, Yuan Qin, Jinglong Liu

“…Additionally, to enhance the model’s attention to licorice at different scales, a Lightweight Multi-Scale Module (LMSM) using multi-scale dilated convolution is introduced, significantly reducing the probability of missed detections. …”
Get full text

Steel surface defect detection method based on improved YOLOv9 by Cong Chen, Hoileong Lee, Ming Chen

“…Second, the C3 module is incorporated to effectively fuse feature maps from different levels, enhancing the model’s ability to detect multi-scale targets. …”
Get full text

DSCONV-GAN: a UAV-BASED model for Verticillium Wilt disease detection in Chinese cabbage in complex growing environments by Jun Zhang, Dongfang Zhang, Jingyan Liu, Yuhong Zhou, Xiaoshuo Cui, Xiaofei Fan

“…Based on YOLOv8, with the addition of the dynamic snake convolution (DSConv) module and the improved loss function maximum possible distance intersection-over-union (MPDIoU), we acquired enhanced complex structures and global characteristics in Chinese cabbage images under different growth conditions. …”
Get full text

A DNA Encoding Image Encryption Algorithm Based on Chaos by Li Huang, Cong Ding, Zhenjie Bao, Haitao Chen, Changsheng Wan

“…This encryption scheme is different from the traditional scrambling and diffusion methods at the level of image spatial pixels but encodes images into DNA strands and completely scrambles and diffuses operations on the DNA strands to ensure the security of images and improve the efficiency of image encryption. …”
Get full text

Towards Synthetic Augmentation of Training Datasets Generated by Mobility-on-Demand Service Using Deep Variational Autoencoders by Martin Gregurić, Filip Vrbanić, Edouard Ivanjko

“…Thus, it generates synthetic samples, known as <i>“deepfakes”</i>. They are added in different percentages to the initial dataset based on real-world MoD-based data. …”
Get full text

Drought Stress Grading Model for Apple Rootstock Softwood Cuttings Based on the CU-ICA-Net by Xu Wang, Pengfei Wang, Jianping Li, Hongjie Liu, Xin Yang

“…The dataset used for model training consists of 1200 RGB images of cuttings under different grades of drought stress. The ratio of the training set to the test set is 1:0.7. …”
Get full text

Optimizing feature extraction and fusion for high-resolution defect detection in solar cells by Hoanh Nguyen, Tuan Anh Nguyen, Nguyen Duc Toan

“…Additionally, our fast multi-scale feature fusion mechanism effectively combines high-resolution details with high-level semantic features from different network layers, optimizing defect detection accuracy. …”
Get full text

Semantic Segmentation of Brain Tumors Using a Local–Global Attention Model by Shuli Xing, Zhenwei Lai, Junxiong Zhu, Wenwu He, Guojun Mao

“…Additionally, the morphology and size of tumors can vary significantly among different patients. These factors pose considerable challenges for the precise segmentation of tumors and subsequent diagnosis. …”
Get full text

Deep Learning-Based Intelligent Detection Algorithm for Surface Disease in Concrete Buildings by Jing Gu, Yijuan Pan, Jingjing Zhang

“…In this study, the extent of concrete building distress is used to determine whether a building needs to be demolished and maintained, and the study focuses on accurately identifying target distress in different complex contexts and accurately distinguishing between their categories. …”
Get full text

Dynamic Calibration and Validation of an Accelerometer Force Balance for Hypersonic Lifting Models by Prakash Singh, Sharad Trivedi, Viren Menezes, Hamid Hosseini

“…Calibration and validation of the balance were carried out by a convolution technique using hammer pulse test and surface pressure measurements. …”
Get full text

HybNet: A hybrid deep models for medicinal plant species identification by B.R. Pushpa, S. Jyothsna, S. Lasya

“…Images captured under unconstrained environments, scale variations, different lighting conditions, leaf orientation, complicated backdrops, and leaflet structure make plant species recognition rigorous and time-consuming. …”
Get full text

A novel multi-scale and fine-grained network for large choroidal vessels segmentation in OCT by Wei Huang, Qifeng Yan, Lei Mou, Yitian Zhao, Wei Chen, Wei Chen, Wei Chen

“…The statistical analysis of these parameters revealed significant differences between the healthy control group and the high myopia group, thereby confirming the value of the proposed work in facilitating subsequent understanding of the disease and clinical decision-making.…”
Get full text

Near-real-time wildfire detection approach with Himawari-8/9 geostationary satellite data integrating multi-scale spatial–temporal feature by Lizhi Zhang, Qiang Zhang, Qianqian Yang, Linwei Yue, Jiang He, Xianyu Jin, Qiangqiang Yuan

“…Specifically, we design a multi-kernel attention-based convolution (MKAC) module for extracting spatial features representing the differences between fire and non-fire pixels within multi-scale receptive fields. …”
Get full text

Dual Attention-Based Global-Local Feature Extraction Network for Unsupervised Change Detection in PolSAR Images by Dazhi Xu, Ming Li, Yan Wu, Peng Zhang, Xinyue Xin

“…First, we use fuzzy C-means clustering on the enhanced Shannon entropy difference image to automatically generate pseudolabeled samples required for unsupervised CD. …”
Get full text

Rice Disease Detection: TLI-YOLO Innovative Approach for Enhanced Detection and Mobile Compatibility by Zhuqi Li, Wangyu Wu, Bingcai Wei, Hao Li, Jingbo Zhan, Songtao Deng, Jian Wang

“…Finally, this study adopted the WIoUv3 loss function and added a dynamic non-monotonic aggregation mechanism to the standard IoU calculation to more accurately evaluate and penalize the difference between the predicted and actual bounding boxes, thus improving the robustness and generalization ability of the model. …”
Get full text

Enhancing ROP plus form diagnosis: An automatic blood vessel segmentation approach for newborn fundus images by José Almeida, Jan Kubicek, Marek Penhaker, Martin Cerny, Martin Augustynek, Alice Varysova, Avinash Bansal, Juraj Timkovic

“…The segmentation pipeline is combined with different pre-trained Convolution Neural Network architectures to evaluate its automatic classification capabilities. …”
Get full text

FD²-YOLO: A Frequency-Domain Dual-Stream Network Based on YOLO for Crack Detection by Junwen Zhu, Jinbao Sheng, Qian Cai

“…Furthermore, the Dynamic Inter-Domain Feature Fusion module (DIFF) is introduced, which uses large-kernel deep convolution and Hadamard to enable the adaptive fusion of features from different domains, thus addressing the problem of difficult feature fusion due to domain differences. …”
Get full text

Super-resolution reconstruction technology for full-diameter core nuclear magnetic resonance scanning data: a global non-negative least squares-based approach by Yingying MA, Zebo PENG, Jingzhi CHEN, Fei WU, Xin NIE, Zhongshu LIAO, Gong ZHANG

“…However, due to its large measurement sensitivity area, signals from different positions overlap, resulting in a significantly lower vertical resolution compared to instrument sampling. …”
Get full text