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检索条件"任意字段=Conference on Image Processing - Algorithms and Systems IV"

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Bacterial Blight and Cotton Leaf Curl Virus Detection Using Inception V4 Based CNN Model for Cotton Crops 5

Bacterial Blight and Cotton Leaf Curl Virus Detection Using ...

引用

5th IEEE International conference on image processing Applications and systems (IPAS)

作者： Anwar, Sohail Kolachi, Abdul Rahim Baloch, Shadi Khan Soomro, Shoaib R. Mehran Univ Engn & Technol Dept Elect Engn Jamshoro Pakistan Mehran Univ Engn & Technol Dept Mechatron Engn Jamshoro Pakistan

ISBN: (纸本)9781665462198

Agriculture sector is an important pillar of the global economy. The cotton crop is considered one of the prominent agricultural resources. It is widely cultivated in India, China, Pakistan, USA, Brazil, and other countries of the world. The worldwide cotton crop production is severely affected by numerous diseases such as cotton leaf curl virus (CLCV/CLCuV), bacterial blight, and ball rot. image processing techniques together with machine learning algorithms are successfully employed in numerous fields and have also used for crop disease detection. In this study, we present a deep learning-based method for classifying diseases of the cotton crop, including bacterial blight and cotton leaf curl virus (CLCV). The dataset of cotton leaves showing disease symptoms is collected from various locations in Sindh, Pakistan. We employ the Inception v4 architecture as a convolutional neural network to identify diseased plant leaves in particular bacterial blight and CLCV. The accuracy of the designed model is 98.26% which shows prominent improvement compared to the existing models and systems.

关键词： cotton crop disease detection CNN CLCV Bacterial Blight detection image processing

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Proceedings - 2023 32nd International conference on Parallel Architecture and Compilation Techniques, PACT 2023

Proceedings - 2023 32nd International Conference on Parallel...

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32nd International conference on Parallel Architecture and Compilation Techniques, PACT 2023

ISBN: (纸本)9798350342543

The proceedings contain 33 papers. The topics discussed include: MBAPIS: multi-level behavior analysis guided program interval selection for microarchitecture studies;automatic code generation for high-performance graph algorithms;SimplePIM: a software framework for productive and efficient processing-in-memory;Drishyam: an image is worth a data prefetcher;architecture-aware currying;PreFlush: lightweight hardware prediction mechanism for cache line flush and writeback;retargeting applications for heterogeneous systems with the tribble source-to-source framework;dynamic allocation of processor cores to graph applications on commodity servers;parallelizing maximal clique enumeration on GPUs;and HugeGPT: storing guest page tables on host huge pages to accelerate address translation.

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2022 International conference on Intelligent systems and Computer Vision, ISCV 2022

2022 International Conference on Intelligent Systems and Com...

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5th International conference on Intelligent systems and Computer Vision, ISCV 2022

ISBN: (纸本)9781665495585

The proceedings contain 71 papers. The topics discussed include: a new sampling strategy to improve the performance of mobile robot path planning algorithms;machine learning based methods for Arabic duplicate question detection;robust traffic signs classification using deep convolutional neural network;image-based visual servoing techniques for robot control;SASHA: a shift-add segmented hybrid approximated multiplier for image processing;graph based method for Arabic text summarization;face information forensics analysis based on facial aging: a survey;advanced financial data processing and labeling methods for machine learning;and recognition system of human activities based on time-frequency features of accelerometer data.

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A New Efficient Split & Merge Algorithm for Embedded systems

A New Efficient Split & Merge Algorithm for Embedded Systems

引用

IEEE International conference on image processing

作者： Nathan Maurice Julien Sopena Lionel Lacassagne LIP6 Sorbonne University Paris

ISBN: (数字)9798350349399

ISBN: (纸本)9798350349405

This article presents a new image segmentation algorithm based on a Split & Merge approach. By nature, the execution time of Split & Merge algorithms is data-dependent, as their halting conditions are tied to the homogeneity of each region. While previous algorithms made the Split step less sensitive to input data, the execution time of the more complex Merge step remains highly sensitive to image content. This paper tackles the sensitivity and performance problems from a system and architecture perspective. Memory reallocations due to array fusions are eliminated with the introduction of a TTA (Three Table Array) structure in the Merge step. As iterating over entries in this structure causes a loss of memory locality, we propose two new mechanisms that implement a software cache to mitigate this. An experimental study on an embedded system (Nvidia Jetson Xavier NX) has shown our Merge algorithm to be 10.6 times faster than the state-of-the-art Split & Merge algorithm for $960 \times 720$ images. Moreover, the execution time of our algorithm is also more resistant to image characteristics.

关键词： Resistance image segmentation Embedded systems Sensitivity Software algorithms Streaming media Prediction algorithms

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Vision Transformer based ResNet Model for Pneumonia Prediction 4

Vision Transformer based ResNet Model for Pneumonia Predicti...

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4th International conference on Electronics and Sustainable Communication systems, ICESC 2023

作者： Sowmya, Thatikonda Sai Narasimhulu, Thumma Sunitha, Gurram Manikanta, Thupakula Venkatesh, Thirupathi Sree Vidyanikethan Engineering College Department of CSE A.P Tirupati India Mohan Babu University School of Computing Department of Ai & Ml A.P Tirupati India

ISBN: (纸本)9798350300093

This research study aims to develop a pneumonia detection system using vision transformers. Pneumonia is a very serious respiratory illness that may result in severe health issues, and early detection is essential for effective treatment. Deep learning-based computer vision algorithms have yielded encouraging results in medical image analysis in recent years, and vision transformers have emerged as a potent tool for processing visual data. The proposed system uses a vision transformer to process chest x-ray images and extract visual traits, which can be utilized for classification. The proposed model 'Vit_base_resnet50_224_in21k' is trained on a vast and diverse dataset of annotated chest x-ray images to understand the patterns and characteristics of pneumonia. The system's performance is estimated using standard evaluation parameters - accuracy, loss, specificity, sensitivity, F1-score and ROC curve. The proposed model has achieved a performance accuracy of 92.96% for pneumonia detection. The results demonstrate the potential of vision transformers in chest x-ray image analysis and contribute to the development of more accurate and efficient tools for pneumonia detection. This system has the potential to assist healthcare professionals in making faster and more accurate diagnosis, which can ultimately improve outcomes and save lives. © 2023 IEEE.

关键词： image analysis

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Face Recognition Implementation Based on image processing Techniques

Face Recognition Implementation Based on Image Processing Te...

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Signal processing and Intelligent Computing (SPIC), International conference on

作者： Bingcan Yang Xiai Chen School of Automation and Electrical Engineering Shenyang Ligong University Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China

ISBN: (数字)9798350368888

ISBN: (纸本)9798350368895

image processing is a technique that involves the manipulation and enhancement of digital images. It encompasses various aspects such as image acquisition, image preprocessing, image enhancement, image segmentation, feature extraction, and object detection. The purpose of image processing is to process and enhance images using computer technology, aiming to achieve higher image quality for subsequent processing and applications. In practical applications, image processing techniques employ different algorithms and methods to achieve various processing and enhancement effects. Additionally, image processing techniques can be applied in fields such as medicine, security, autonomous driving, VR/AR, etc. For instance, in the medical field, image processing techniques can be utilized for image segmentation and diagnosis of medical images, thereby improving the accuracy and analytical capabilities of medical imaging. In the security field, image processing techniques can be employed for tasks such as video surveillance and facial recognition, enhancing the efficiency and accuracy of security monitoring. In the domain of autonomous driving, image processing techniques can be used for detecting and recognizing the surrounding environment of vehicles, thereby enhancing the safety and performance of autonomous driving systems. In conclusion, image processing technology is a very important technology. By continuously improving the accuracy and reliability of the algorithm, it is expected to be applied in a wider range of applications.

关键词： image segmentation image recognition Accuracy image processing Face recognition Signal processing algorithms Signal processing Video surveillance Medical diagnostic imaging Autonomous vehicles

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Direction-of-arrival estimation with new versions of Min-Norm algorithm based on Nyström method 7

Direction-of-arrival estimation with new versions of Min-Nor...

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7th International conference on image and Signal processing and their Applications, ISPA 2022

作者： Naceur, Aounallah Ali, Khalfa Kasdi Merbah University Faculty of New Information Technologies and Communication Department of Electronic and Telecommunications Ouargla30000 Algeria Mohamed Boudiaf University Faculty of Technologies Department of Electronic M'Sila28000 Algeria

ISBN: (纸本)9781665480420

Direction-of-arrival estimation is a significant problem in many telecommunication systems which their architecture is composed with antenna arrays. In literature, several algorithms were proposed as a challenge, for different scenarios, to detect rapidly and accurately the direction of impinging signals on the antenna array. In this paper firstly, we use the Nyström method to develop a low computational Min-Norm version for solving the problem of direction-of-arrival estimation by spectral peak searching. Then, we generalize the root version of the proposed algorithm. Finally, we give some simulation results for demonstrating the efficiency and the performances of the new proposed algorithm versions. © 2022 IEEE.

关键词： Array processing

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Computer-Aided Audit Software Based on Fuzzy Clustering Algorithm

Computer-Aided Audit Software Based on Fuzzy Clustering Algo...

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image processing and Computer Applications (ICIPCA), IEEE International conference on

作者： Yuan Fen Wuhan Qingchuan University Wuhan City Hubei Province China

ISBN: (数字)9798350360240

ISBN: (纸本)9798350384161

According to the needs of auditing work, efforts are made to develop suitable computer-aided auditing software to gradually change or enhance traditional auditing techniques and methods, which can better play the role of audit supervision. The purpose of this paper is to study the design and optimisation of computer-aided audit software based on fuzzy clustering algorithms. By analysing the technical difficulties of computer-aided auditing, this paper proposes the design concept of the project software. The improved fuzzy C-mean clustering algorithm DFCM and the fast audit steps of the project based on improved fuzzy clustering are specifically introduced, and the data processing methods of the system are described in detail, and the specific application of the project software is also presented. The experimental results show that the computer-aided audit software in this paper can be applied to calculate the audit price of the project to be audited and the software is feasible.

关键词： image processing Software algorithms Clustering algorithms Quality control Data warehouses Data processing Software Protection Expert systems Optimization

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Comparison and Application of Vehicle Target Detection Methods Based on YOLOv5s and YOLOv7 7

Comparison and Application of Vehicle Target Detection Metho...

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7th IEEE International conference on Information systems and Computer Aided Education, ICISCAE 2024

作者： Gu, Chenyu Du, Hong Zhang, Xiaozheng Li, Lidan Yang, Zhonglin Liu, Gaotian China Northern Vehicle Research Institute Beijing China

ISBN: (纸本)9798350350760

Currently, the methods for pedestrian detection have undergone significant expansion, yet vehicle target detection still retains immense potential for widespread application in the field of intelligent recognition. Nevertheless, vehicle target detection encounters challenges in terms of detection effectiveness, impacted by factors such as lighting conditions, environmental variations, and occlusions. This study centers on vehicle target detection, aiming to tackle the issues of difficult detection, easy missed detection, and algorithm selection within complex backgrounds. By utilizing the YOLOv5s and YOLOv7 algorithms, we have constructed a dataset that encompasses images featuring vehicles against complex backgrounds and in small scales. This dataset is then used to train the models, which are subsequently employed to perform target recognition for vehicles individually. Through comparative experimentation, we have proven the superiority of the YOLOv7 algorithm in detecting vehicles amidst complex backgrounds and those of small scales. ©2024 IEEE.

关键词： image processing vehicle target detection YOLOv5s YOLOv7

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A Fast image Mosaic Algorithm Based on Feature Partition Extraction

A Fast Image Mosaic Algorithm Based on Feature Partition Ext...

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image processing, Electronics and Computers (IPEC), Asia-Pacific conference on

作者： Zhiyou Lian Jianhua Ren School of Electronics and Information Engineering Liaoning University of Engineering and Technology Huludao Liaoning China

ISBN: (数字)9798350374407

ISBN: (纸本)9798350374414

This paper proposes a fast image stitching algorithm based on feature partitioning extraction to address the issues of long processing time, high computational complexity, and poor stitching performance in existing image stitching algorithms. This algorithm is implemented through two stages: optimizing image registration and image fusion. In the image registration stage, feature extraction and accumulation are carried out using image partitioning and an improved Gaussian pyramid layer series method; In the image fusion stage, an improved adaptive weighted average fusion algorithm is used for image fusion operations to improve stitching efficiency and make the image clearer and more natural. Experimental verification shows that the algorithm has strong robustness, significantly improving feature extraction speed and matching rate. Compared with mainstream algorithms, the stitching speed has increased by nearly 2 times, and the image related evaluation indicators have increased by about $5 \%$, basically meeting the real-time and timely needs of image stitching in daily life.

关键词： image registration Deformation Feature extraction Robustness Real-time systems Partitioning algorithms Computational complexity image stitching image fusion image reconstruction

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