Cancer survival prediction is pivotal in tailoring individualized treatment strategies and guiding clinician decision-making. Yet, existing methodologies grapple with efficiently harnessing the intricate distribution ...
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Named Entity Recognition (NER) is one of the crucial and vital subtasks that must be solved in most Natural Language Processing (NLP) tasks. However, constructing a NER system for the Sinhala Language is challenging. ...
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Developments in new-generation information technology have enabled Digital Twins to reshape the physical world into a virtual digital space and provide technical support for constructing the *** objects can be at the ...
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Developments in new-generation information technology have enabled Digital Twins to reshape the physical world into a virtual digital space and provide technical support for constructing the *** objects can be at the micro-,meso-,or *** Metaverse is a complex collection of solid,liquid,gaseous,plasma,and other uncertain ***,the Metaverse integrates tangibles with social relations,such as interpersonal(friends,partners,and family)and social relations(ethics,morality,and law).This review introduces some principles and laws,such as broken windows theory,small-world phenomenon,survivor bias,and herd behavior,for constructing a Digital Twins model for social ***,from multiple perspectives,this article reviews mappings of tangible and intangible real-world objects to the Metaverse using the Digital Twins model.
Genomic variants, which can disrupt cellular functions, present a challenge in distinguishing deleterious from benign instances. While assessing genome-wide functional impacts, many current algorithms neglect protein ...
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Wearing a safety helmet at the work site of a chemical plant can effectively prevent safety accidents caused by head injuries, so it is very important to detect whether employees wear safety helmets. In order to solve...
Wearing a safety helmet at the work site of a chemical plant can effectively prevent safety accidents caused by head injuries, so it is very important to detect whether employees wear safety helmets. In order to solve problems such as serious information loss, large number of parameters, and weak detection ability of small targets in complex scenes in the sampling process of helmet detection algorithm. In this paper, an improved lightweight safety helmet detection algorithm LP- YOLOv5m (Lightweight And High Precision YOLOv5m) based on YOLOv5m is designed. LP-YOLOv5m incorporates the Wise-IoU (Wiou) loss function to enhance model generalization. Additionally, we add a small object detection layer to improve the feature extraction ability for small objects. Furthermore, upsampling was performed using CARAFE. Finally, a lightweight module named C3-F was proposed, which replaced the Bottleneck in the C3 module with FasterNet Block, which could effectively reduce the network model size. Comparative laboratory findings demonstrate that our improved model achieves a mAP50 of 92.1%, surpassing YOLOv5m by 3 percentage points while reducing the model size by 23.3%. The LP-YOLOv5m model can be better applied to practical scene requirements, and can effectively solve practical problems.
The research project focuses on prototyping an IoT (Internet of Things) system for measuring and monitoring the quality of the Wang River in Lampang Municipality. The system utilizes EC (Electrical Conductivity), pH, ...
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GhostNet is proposed by Huawei Noah’s Ark Laboratory in CVPR2020, which can be used with the same accuracy, with less speed and less computation than SOTA method. This convolution is a low-cost operation used to decr...
GhostNet is proposed by Huawei Noah’s Ark Laboratory in CVPR2020, which can be used with the same accuracy, with less speed and less computation than SOTA method. This convolution is a low-cost operation used to decrease the amount of computation and related parameters. Ghost convolution can be used as an alternative to traditional convolution operations because they have the same accuracy. However, utilize significantly less computation and a much smaller parameter count. GSConv(Group-Shared Convolution) is a convolution operation based on group shared weights. This operation achieves efficient parallel convolution operations by grouping convolution kernels. In this way, the parameters used and calculation complexity of the model can be reduced to some extent. This makes the network more computationally efficient and smaller in model size while maintaining accuracy. The algorithm can detect the location of protective clothing quickly and efficiently, and its accuracy and efficiency have been verified. Because the algorithm adopts lightweight network structure, real-time detection can be realized on lowpower devices efficiently. The model architecture enhances the performance based on the YOLOv5 target detection algorithm by incorporating additional features. So that the model can maintain a high precision, which is crucial for the protective clothing detection algorithm.
Medical Image Analysis(MIA)is one of the active research areas in computer vision,where brain tumor detection is the most investigated domain among researchers due to its deadly *** tumor detection in magnetic resonan...
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Medical Image Analysis(MIA)is one of the active research areas in computer vision,where brain tumor detection is the most investigated domain among researchers due to its deadly *** tumor detection in magnetic resonance imaging(MRI)assists radiologists for better analysis about the exact size and location of the ***,the existing systems may not efficiently classify the human brain tumors with significantly higher *** addition,smart and easily implementable approaches are unavailable in 2D and 3D medical images,which is the main problem in detecting the *** this paper,we investigate various deep learning models for the detection and localization of the tumor in MRI.A novel twotier framework is proposed where the first tire classifies normal and tumor MRI followed by tumor regions localization in the second ***,in this paper,we introduce a well-annotated dataset comprised of tumor and normal *** experimental results demonstrate the effectiveness of the proposed framework by achieving 97%accuracy using GoogLeNet on the proposed dataset for classification and 83%for localization tasks after finetuning the pre-trained you only look once(YOLO)v3 model.
The cross-modal person re-identification task aims to match visible and infrared images of the same individual. The main challenges in this field arise from significant modality differences between individuals and the...
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In view of the safety hazards existing on campus, a campus safety detection system based on deep learning behavior recognition, license plate recognition and speed detection is proposed and designed. The design divide...
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