Enhancing Tomato Leaf Disease Detection via Optimized VGG16 and Transfer Learning Techniques by Sandy Putra Siregar, Imam Akbari, Poningsih Poningsih, Anjar Wanto, Solikhun Solikhun

“…This paper offers an improved CNN through hyperparameter tuning and compares it to Transfer Learning models such as InceptionV3, NASNetMobile, and VGG16, which were chosen for their efficiency and accuracy. …”
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Research on the lightweight detection method of rail internal damage based on improved YOLOv8 by Xiaochun Wu, Shuzhan Yu

“…The model achieves an optimal balance between detection accuracy and computational efficiency, addressing the railroad industry’s demand for real-time defect detection and ensuring accurate flaw identification in resource-constrained Rail Fault Detection (RFD) vehicles.…”
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Risk Prediction of Coal and Gas Outburst Based on Abnormal Gas Concentration in Blasting Driving Face by Liming Qiu, Yujie Peng, Dazhao Song

“…There are strong correlations between the growth rate, peak value, and decay rate of gas concentration after blasting and K1 value, and the maximum correlation coefficient is 0.92. Using the prediction model, 28 times of jet holes and 1 small outburst event are predicted successfully, and the efficiency of the prediction model is 76.39%. …”
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An Innovative Method of Monitoring Cotton Aphid Infestation Based on Data Fusion and Multi-Source Remote Sensing Using Unmanned Aerial Vehicles by Chenning Ren, Bo Liu, Zhi Liang, Zhonglong Lin, Wei Wang, Xinzheng Wei, Xiaojuan Li, Xiangjun Zou

“…Accordingly, there is a pressing need for efficient and high-precision UAV remote sensing technology for effective identification and localization. …”
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Use of deep learning in early software bug detection by Syed Mibran Hassan Zaidi, Maria Khan, Mustafa Latif, Ali Akhtar, Sallar Khan

“…Therefore, an efficient software bug detection model is a critically significant challenging operation, and that has been developed in this work by designing the efficient model while using the promises dataset as input for bug identification. …”
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Crack Detection Method of Sleeper Based on Cascade Convolutional Neural Network by Liming Li, Shubin Zheng, Chenxi Wang, Shuguang Zhao, Xiaodong Chai, Lele Peng, Qianqian Tong, Ji Wang

“…This work presents a new method for sleeper crack identification based on cascade convolutional neural network (CNN) to address the problem of low efficiency and poor accuracy in the traditional detection method of sleeper crack identification. …”
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Enhancing the e-commerce shopping experience with IoT-enabled smart carts in smart stores by Jian Wang

“…A neuro-fuzzy approach is employed to evaluate the efficiency of the proposed model. The neural network model is trained using a dataset split into three segments: 65% for training, 15% for validation, and 20% for testing. …”
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Harnessing self-supervised learning to boost malicious traffic detection with enhanced attention by SUN Jianwen, ZHANG Bin, LI Hongyu, CHANG Heyu

“…Before making classification decisions, the integration ability of high-weight features was enhanced to further improve the model's detection precision. The CIC-IDS2017 dataset was employed for the experiment, and the results showed that in the multi-classification scenario for malicious traffic identification, the precision of the MTAttention method could reach an average of 98.7%, and the inference efficiency exceeded 1590 samples per second. …”
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RP-DETR: end-to-end rice pests detection using a transformer by Jinsheng Wang, Tao Wang, Qin Xu, Lu Gao, Guosong Gu, Liangquan Jia, Chong Yao

“…In precision agriculture, fast and accurate automatic pest identification is essential. To tackle this issue, multiple models utilizing computer vision and deep learning have been applied. …”
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Artificial intelligence in suicide prevention: Utilizing deep learning approach for early detection by Vikas Gaur, Gaurav Maggu, Khushboo Bairwa, Suprakash Chaudhury, Sana Dhamija, Tahoora Ali

“…High precision, recall, and accuracy align with expert evaluations, highlighting its promise for timely risk identification. The model’s efficiency in evaluating large populations swiftly indicates its clinical potential. …”
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Enhancing Intelligent Road Target Monitoring: A Novel BGS-YOLO Approach Based on the YOLOv8 Algorithm by Xingyu Liu, Yuanfeng Chu, Yiheng Hu, Nan Zhao

“…Additionally, this paper innovatively designs the SimAM-C2f (SimC2f) network, further advancing feature expressiveness and fusion efficiency. Experiments on the public COCO dataset demonstrate that the BGS-YOLO model significantly outperforms the existing YOLOv8n model. …”
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Ocean Internal Wave Detection in SAR Images Based on Improved YOLOv7 by Limei Cai, Guozhen Zha, Mingsen Lin, Xiao Wang, Honghua Zhang

“…To improve the accuracy and efficiency of ocean internal wave identification, this paper proposes an automatic identification technique based on YOLOv7, which can quickly and accurately extract the signatures of ocean internal waves from a large amounts of SAR (Synthetic Aperture Radar) images, and realize the efficient identification of ocean internal waves. …”
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Safety helmet detection methods in heavy machinery factory by Liu Baoju, Wei Xiangqian, Chen Qingshan, Liu Jiaqi, Chen Ye, Yu Peng, Lei shi, Hu Yongfeng

“…In light of this, this paper presents an improved model based on YOLOv10 to achieve safety helmet identification. …”
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Algorithm of Development for Stabilization of Socio-Ecological Situation in Karakalpakstan by Alisher Abdullaev

“…The parameters of the developed mathematical model and their adequacy are determined. The developed mathematical model will allow identification of the social and ecological situation of the republic. …”
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LiteTom-RTDETR: A Lightweight Real-Time Tomato Detection System for Plant Factories by Wenshuai Liu, Qingzheng Liu, Wenyong Quan, Junli Wang, Xiaomin Yao, Qiang Liu, Yuxiang Tian

“…The proposed LiteTom-RTDETR model was shown to balance high tomato identification accuracy (88.2%) with an excellent real-time inference speed (52.2 frames per second) and computational efficiency (36.3 GFLOPs). …”
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Building construction crack detection with BCCD YOLO enhanced feature fusion and attention mechanisms by Wenhao Ren, Zuowei Zhong

“…This contributes to the accurate and timely identification of structural cracks, thereby enhancing maintenance efficiency and preventing potential failures in building construction.…”
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Research on the generation and annotation method of thin section images of tight oil reservoir based on deep learning by Tao Liu, Zongbao Liu, Kejia Zhang, Chunsheng Li, Yan Zhang, Zihao Mu, Mengning Mu, Mengting Xu, Yue Zhang, Xue Li

“…The use of deep learning technology for intelligent identification of thin section images is a development trend of mineral identification. …”
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EER-DETR: An Improved Method for Detecting Defects on the Surface of Solar Panels Based on RT-DETR by Jiajun Dun, Hai Yang, Shixin Yuan, Ying Tang

“…In the context of the rapid popularization of clean energy, the precise identification of surface defects on photovoltaic modules has become a core technical bottleneck limiting the operational efficiency of power stations. …”
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A New Contact Force Estimation Method for Heavy Robots Without Force Sensors by Combining CNN-GRU and Force Transformation by Peizhang Wu, Hui Dong, Pengfei Li, Yifei Bao, Wei Dong, Lining Sun

“…This method can achieve robot end contact force estimation without a force sensor, avoiding the cumbersome manual modeling and identification process. Compared with traditional manual modeling and identification methods, experiments show that the proposed method in this paper can approximately double the estimation accuracy of the contact force of heavy robots and reduce the time consumption by approximately half, with advantages such as convenience, efficiency, strong real-time performance, and high accuracy.…”
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A Fast Recognition Method for Dynamic Blasting Fragmentation Based on YOLOv8 and Binocular Vision by Ming Tao, Ziheng Xiao, Yulong Liu, Lei Huang, Gongliang Xiang, Yuanquan Xu

“…The dynamic recognition Mean Average Precision of this integrated model is 0.84, providing a valuable reference for evaluating blasting effects and improving work efficiency.…”
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