High-Accuracy Recognition Method for Diseased Chicken Feces Based on Image and Text Information Fusion by Duanli Yang, Zishang Tian, Jianzhong Xi, Hui Chen, Erdong Sun, Lianzeng Wang

“…Conventional visual-only methods face limitations due to environmental sensitivity and high visual similarity among feces from different diseases. To address this, we propose MMCD (Multimodal Chicken-feces Diagnosis), a ResNet50-based multimodal fusion model leveraging semantic complementarity between images and descriptive text to enhance diagnostic precision. …”
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Development of IIOT-Based Pd-Maas Using RNN-LSTM Model with Jelly Fish Optimization in the Indian Ship Building Industry by PNV Srinivasa Rao, PVY Jayasree

“…The validation of the proposed predictive maintenance model optimization with different types of deep learning algorithms shows that our proposed methodology gives an improved accuracy of 98.9336% which is higher than any other models.   …”
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AGCN-T: A Traffic Flow Prediction Model for Spatial-Temporal Network Dynamics by Jian Feng, Lang Yu, Rui Ma

“…In the spatial dependency extraction module, according to the similarity of historical traffic flow sequences of different loop detectors, an adjacency matrix for the road network is constructed based on a sequence similarity calculation method, Predictive Power Score (PPS), to express latent spatial dependency; and then GCN is used on the adjacency matrix to capture the global spatial correlation and Transformer is used to capture dynamic spatial dependency from the most recently flow sequences. …”
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A Novel Two-Level Protection Scheme against Hardware Trojans on a Reconfigurable CNN Accelerator by Zichu Liu, Jia Hou, Jianfei Wang, Chen Yang

“…With the boom in artificial intelligence (AI), numerous reconfigurable convolution neural network (CNN) accelerators have emerged within both industry and academia, aiming to enhance AI computing capabilities. …”
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Advancing malware imagery classification with explainable deep learning: A state-of-the-art approach using SHAP, LIME and Grad-CAM. by Sadia Nazim, Muhammad Mansoor Alam, Syed Safdar Rizvi, Jawahir Che Mustapha, Syed Shujaa Hussain, Mazliham Mohd Suud

“…Whereas AI has countless benefits, its convoluted and sometimes vague internal operations can establish difficulties. …”
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Efficient Hybrid Deep Learning Model for Battery State of Health Estimation Using Transfer Learning by Jinling Ren, Misheng Cai, Dapai Shi

“…The proposed method not only achieves high-precision SOH estimation among the same type of batteries but also demonstrates strong generalization ability under different battery chemistries and scenarios.…”
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Recognition Method of Corn and Rice Crop Growth State Based on Computer Image Processing Technology by Li Tian, Chun Wang, Hailiang Li, Haitian Sun

“…The fuzzy mathematical model is also devised to identify the characteristics of crops in different growth periods and to complete the identification of growth state. …”
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Resilience Analysis of Urban Road Networks Based on Adaptive Signal Controls: Day-to-Day Traffic Dynamics with Deep Reinforcement Learning by Wen-Long Shang, Yanyan Chen, Xingang Li, Washington Y. Ochieng

“…In this study, red time split is regarded as extra traffic flow to discourage drivers to use affected roads, so as to reduce congestion and improve the resilience when urban road networks are subject to different levels of disruptions. In addition, we utilize the convolution neural network as Q-network to approximate Q values, link flow distribution and link capacity are regarded as the state space, and actions are denoted as red/green time split. …”
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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. …”
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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. …”
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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. …”
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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. …”
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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. …”
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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. …”
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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. …”
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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. …”
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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. …”
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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. …”
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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. …”
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MAS-YOLOv11: An Improved Underwater Object Detection Algorithm Based on YOLOv11 by Yang Luo, Aiping Wu, Qingqing Fu

“…By employing learnable spatial weighting parameters, ASFFHead adaptively fuses features across different scales, significantly improving the robustness of multi-scale object detection. …”
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