Advanced Detection of Violence From Video: Performance Evaluation of Transformer and State of the Art of Convolution of Neural Network Transformer by Abdulrahman Alshalawi, Wadood Abdul, Ghulam Muhammad

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Automated detection of Parkinson’s disease using improved linknet-ghostnet model based on handwriting images by P Pradeep, J Kamalakannan

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Enhancing Speaker Recognition with CRET Model: a fusion of CONV2D, RESNET and ECAPA-TDNN by Pinyan Li, Lap Man Hoi, Yapeng Wang, Xu Yang, Sio Kei Im

“…To further improve the accuracy of the model, better capture the temporal context information, and make ECAPA-TDNN unaffected by small offsets in the frequency domain, based on the ECAPA-TDNN model, we combine a two-dimensional convolutional network (Conv2D), a residual network (ResNet), and ECAPA-TDNN to form a novel CRET model. …”
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Enhancing Real-Time Road Object Detection: The RD-YOLO Algorithm With Higher Precision and Efficiency by Weijian Wang, Wei Yu

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Majority clustering for imbalanced image classification by Keshav Sharma, Jyoti Arora, Pooja Kherwa, Zainab Alansari

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A Comparative Study of YOLO, SSD, Faster R-CNN, and More for Optimized Eye-Gaze Writing by Walid Abdallah Shobaki, Mariofanna Milanova

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Research on the Real-Time Scoring of Chest Ring Target Based on Transfer Learning and Improved Lightweight Neural Network by Minghui Meng, Chuande Zhou

“…First, the Repvit-MobileNet block (re-parameterized depth wise separable mobile network module) is introduced into its backbone network to reduce model size and computational complexity while improving detection speed. …”
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AirTrace-SA: Air Pollution Tracing for Source Attribution by Wenchuan Zhao, Qi Zhang, Ting Shu, Xia Du

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Research on Fault Detection Technology for Circuit Breaker Operating Mechanism Combinations Based on Deep Residual Networks by Hongping Shao, Yizhe Jiang, Jianeng Zhao, Xueteng Li, Mingzhan Zhang, Mingkun Yang, Xinyu Wang, Hao Yang

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Brain Tumor Classification of Medical Images based on Transfer Pre-trained Learning Models by Mohamed H Ghaleb Abdkhaleq Abdkhaleq, Ibraheem Al-Jadir, Loay George, Yuri Yuryevich Gromov, Eliseev Aleksey Igorevich

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A deep neural network with attention mechanism for flow prediction of compressor blade by Guanyu Gao, Gang Wang

“…Motivated by this tricky issue, a convolutional neural network (CNN) based on U-Net architecture with attention mechanism (AM) is proposed to efficiently learn flow representations from CFD results to shorten the compressor blade design cycle. …”
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Leveraging internet use for sustainable agriculture: the impact of digital training on adoption of energy-smart agricultural practices and welfare by Ali Sher, Saman Mazhar, Dil Bahadur Rahut, Hongping Yuan

“…Our results from the selection equation indicate that access to an internet connection, positive perceptions of internet information, social networks, gender (male), farm size, off-farm income, livestock holdings, and membership in farmer-based organizations (FBOs) are significantly associated with participation in digital training. …”
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The analysis of spring wheat productivity by the method of principal component by R. I. Ibyatov, F. Sh. Shaykhutdinov, A. A. Valiev

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Approach for enhancing the accuracy of semantic segmentation of chest X-ray images by edge detection and deep learning integration by Lesia Mochurad

“…These results consistently outperform the baseline U-net model without edge enhancement.DiscussionThe integration of contour detection methods with the U-net model significantly improves the segmentation quality of complex anatomical regions in chest X-rays. …”
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Bangla Character Detection Using Enhanced YOLOv11 Models: A Deep Learning Approach by Mahbuba Aktar, Nur Islam, Chaoyu Yang

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A compact deep learning approach integrating depthwise convolutions and spatial attention for plant disease classification by Amreen Batool, Jisoo Kim, Yung-Cheol Byun

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An improved lightweight tiny-person detection network based on YOLOv8: IYFVMNet by Fan Yang, Lihu Pan, Hongyan Cui, Linliang Zhang

“…This approach fully utilizes all feature map information while minimizing the computational and memory requirements. (2) the neck network structure is optimized using the Vovnet Gsconv Cross Stage Partial module. …”
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Evaluating the use of automated plant identification tools in biodiversity monitoring—a case study in Switzerland by Manuel R. Popp, Niklaus E. Zimmermann, Philipp Brun

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Lightweight tea bud detection method based on improved YOLOv5 by Kun Zhang, Bohan Yuan, Jingying Cui, Yuyang Liu, Long Zhao, Hua Zhao, Shuangchen Chen

“…The following methods are used to make improvements: the backbone network CSPDarknet-53 of YOLOv5 is replaced with the EfficientNetV2 feature extraction network to reduce the number of parameters and floating-point operations of the model; the neck network of YOLOv5, the Ghost module is introduced to construct the ghost convolution and C3ghost module to further reduce the number of parameters and floating-point operations of the model; replacing the upsampling module of the neck network with the CARAFE upsampling module can aggregate the contextual tea bud feature information within a larger sensory field and improve the mean average precision of the model in detecting tea buds. …”
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The heterogeneous roles of neutrophils in gastric cancer: scaffold or target? by Yansong Qin, Yunmei Liu, Peixin Dong, Wen-Bin Zou, Zhaoshen Li, Lei Huang

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