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检索条件"任意字段=3rd International Conference on Computer Vision and Image Processing, CVIP 2018"

共 1647 条记录，以下是241-250 订阅

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Dermatobot: An image processing Enabled Chatbot for Diagnosis and Tele-remedy of Skin Diseases 3

Dermatobot: An Image Processing Enabled Chatbot for Diagnosi...

引用

3rd international conference for Emerging Technology, INCET 2022

作者： Kohli, Shivansh Verma, Utkarsh Kirpalani, Vinay V Srinath, Ramamoorthy Pes University Computer Science and Engineering Karnataka Bangalore India

ISBN: (纸本)9781665494991

Diseases of dermatological nature have become quite common given the deteriorating environmental conditions, making visits to a dermatologist more frequent. However, a visit to a dermatologist may not always be very feasible as a result of which skin diseases may go untreated and this might become a significant problem in time. Dermatobot is a portable dermatologist for common skin diseases which aims at reducing skin ailments going untreated by providing a combined computer vision and NLP enabled diagnosis to skin diseases and suggesting out remedies for the diagnosed disease. Universal Sentence Encoders were used for similarity matching and an image classification model trained upon EfficientNetB4. The image classification model obtained a top-5 validation accuracy of 92%.Disclaimer: Dermatobot is not a replacement for dermatologists and only recommends mild remedies that the user can adhere to at his/her own avail. © 2022 IEEE.

关键词： Telemedicine

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Mouse Neuroimaging Phenotyping in the Cloud

Mouse Neuroimaging Phenotyping in the Cloud

引用

3rd international conference on image processing Theory, Tools and Applications (IPTA)

作者： Minervini, Massimo Damiano, Mario Tucci, Valter Bifone, Angelo Gozzi, Alessandro Tsaftaris, Sotirios A. IMT Inst Adv Studies Lucca Lucca Italy

ISBN: (纸本)9781467325851;9781467325837

The combined use of mice that have genetic mutations (transgenic mouse models) of human pathology and advanced neuroimaging methods (such as MRI) has the potential to radically change how we approach disease understanding, diagnosis and treatment. Morphological changes occurring in the brain of transgenic animals as a result of the interaction between environment and genotype, can be assessed using advanced image analysis methods, an effort described as "mouse brain phenotyping". However, the computational methods required for the analysis of high-resolution brain images are demanding. In this paper, we propose a computationally effective cloud-based implementation of morphometric analysis of high-resolution mouse brain datasets. We show that the proposed approach is highly scalable and suited for a variety of methods for MR-based brain phenotyping. The proposed approach is easy to deploy, and could become an alternative for laboratories that may require instant access to large high performance computing infrastructure.

关键词： High performance computing cloud neuroimaging MRI phenotyping computer vision image analysis

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Dermatological Disease Detection Using image processing and Machine Learning 3

Dermatological Disease Detection Using Image Processing and ...

引用

3rd international conference on Artificial Intelligence and Pattern Recognition (AIPR)

作者： Kumar, Vinayshekhar Bannihatti Kumar, Sujay S. Saboo, Varun PES Inst Technol Dept Comp Sci Bengaluru Karnataka India

ISBN: (纸本)9781467391870

Dermatological diseases are the most prevalent diseases worldwide. Despite being common, its diagnosis is extremely difficult and requires extensive experience in the domain. In this research paper, we provide an approach to detect various kinds of these diseases. We use a dual stage approach which effectively combines computer vision and Machine Learning on clinically evaluated histopathological attributes to accurately identify the disease. In the first stage, the image of the skin disease is subject to various kinds of pre-processing techniques followed by feature extraction. The second stage involves the use of Machine learning algorithms to identify diseases based on the histopathological attributes observed on analysing of the skin. Upon training and testing for the six diseases, the system produced an accuracy of up to 95 percent.

关键词： Dermatology image processing computer vision Machine Learning Data Mining Computational Intelligence Automated Disease Diagnosis

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A low illumination image enhancement algorithm based on adaptive fractional differentiation 3

A low illumination image enhancement algorithm based on adap...

引用

3rd international conference on computer Information Science and Application Technology (CISAT)

作者： Wang, Liangyan Zhan, Xiaoyi Wang, Chunling Chen, Zihong Xia, Yunfei Anhui Sanlian Univ Sch Robot Engn Hefei 230601 Anhui Peoples R China

Using fixed order fractional differential for image enhancement, some regions of the image may not achieve the desired enhancement effect. According to the characteristics of human vision and low illumination image, an adaptive order fractional differential enhancement algorithm is proposed. Three different differential orders are selected for enhancement, and one of them is adaptively selected for each pixel according to the comparison results of gradient values. The experimental results show that the adaptive order can not only enhance the image with high gradient value such as the edge, but also reduce the noise interference in the flat area,which has better visual effect than fixed order enhancement.

关键词： image enhancement

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Single-Photon Cameras image Reconstruction Using vision Transformer 3

Single-Photon Cameras Image Reconstruction Using Vision Tran...

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3rd IEEE international conference on computer Communication and Artificial Intelligence, CCAI 2023

作者： Wang, Xingzheng Beijing Institute of Technology Beijing China

ISBN: (纸本)9798350335262

Single-photon camera is a novel camera type that utilizes image sensor with photon-counting capability. Recently, the potential of such sensors to achieve high spatial resolutions (e.g., 10/chip) and frame rates (e.g., 10/sec) is well-established. However, there is a significant difference in the output data between single-photon cameras and traditional CMOS sensor cameras. Therefore, conventional image reconstruction algorithms cannot be utilized. Vison Transformer has impressive performance on image processing tasks, and this paper will design a plug-and-play algorithm for reconstructing images from single-photon cameras and integrate image processing algorithms based on deep neural networks like ViT. The results demonstrate our methods can achieve improvement both in PSNR and SSIM. © 2023 IEEE.

关键词： Cameras

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Moving Vehicle Detection Using Haar-like, LBP and a Machine Learning Adaboost Algorithm 3

Moving Vehicle Detection Using Haar-like, LBP and a Machine ...

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3rd IEEE international conference on image processing, Applications and Systems, IPAS 2018

作者： Jabri, S. Saidallah, M. El Belrhiti El Alaoui, A. El Fergougui, A. Computer Networks and Systems Laboratory FSM-UMI BP 11201 Meknes Morocco

ISBN: (纸本)9781728102474

Object detection and classification is one of the core functions of Intelligence Transport Systems (ITS). It is typically based on extracted features and learning algorithms. Different approaches seem to be appropriate. Researchers should compare and evaluate existing approaches to apply the most efficient. In this paper, we propose a moving vehicle-detection vision system. Two solutions are examined in terms of performance and energy-efficient. The first is a classical Adaboost approach based on the Haar-like in feature extraction whereas the second handles a Local Binary Pattern descriptor that will undergo extraction with Adaboost classifier. Comparison results are illustrated based on the GTI vehicle image dataset. The most pertinent is the Haar-like +Adaboost, leading a DR of 90.1% instead of 87.9% for the LBP+Adaboost. However, LBP+Adaboost shows a low energy consumption, which is very important in any embedded systems. © 2018 IEEE.

关键词： Local binary pattern

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A Real-time Fire Detection and Notification System Based on computer vision

A Real-time Fire Detection and Notification System Based on ...

引用

3rd international conference on IT Convergence and Security (ICITCS)

作者： Bayoumi, Sahar AlSobky, Elham Almohsin, Moneerah Altwaim, Manahel Alkaldi, Monira Alkahtani, Munera Univ Alexandria Inst Gradute Studies & Res Alexandria Egypt King Saud Univ Coll Comp & Informat Technol Riyadh 11421 Saudi Arabia

ISBN: (纸本)9781479928453

Fires are one of the main causes of death amongst the world. Although there are various fire detection systems most of them did not proof its effectiveness in detecting fires due to inefficiency or restrictions. For example, systems based on smoke sensors in detecting fires cannot be used in open areas because they are restricted to the existence of a ceiling or a wall. Besides that, having many flammable objects in open large areas, such as trees and fuel of car may interact with oxygen in the air which make fire growth and expansion very fast. According to the prior stated facts in this paper we present the project we worked on with the aim of implementing a more efficient and trustworthy fire detecting system. The project was done by using computer vision and image processing techniques to detect fire flames based on studying the fire properties besides an alarm notification system.

关键词： computer vision image processing Real time detection Fire detection Notification system

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Edge detection for online image processing of a vision guide pick and place robot 3

Edge detection for online image processing of a vision guide...

引用

3rd international conference on Electrical Engineering and computer Science (ICECOS)

作者： Qul'am, Hasta Muzana Dewi, Tresna Risma, Pola Oktarina, Yurni Permatasari, Dewi Politekn Negeri Sriwijaya Elect Engn Dept Palembang Indonesia

ISBN: (纸本)9781728147147

Robotics technology has merged into human's ev-eryday life, from industry to domestic application, including agriculture and creates digital farming. Agriculture industry currently faces new challenges, including aging farming and higher demand for food to feed the growing population. It is expected that robot application in agriculture can reduce the production cost in the long run and improve product quality, and increase productivity. A robot can be applied from seeding, maintenance, crop harvesting, and packing. A pick and place robot is an ideal form in accumulation and packing the harvested product. This type of robot a vision sensor to detect the crop to be collected or object to be picked and placed. However, the application of image processing needs to be kept adequate but straightforward to accommodate the current microcontroller technology. This paper discusses the implementation of an edge detection method for recognizing and tracking an object, and the target considered in this study is a tomato. Twenty experiments were conducted to pick and place a tomato from 3 random positions to a basket. The total average time of robot to finish its task is 05.81 s. The experimental result shows that the proposed method is effective for a 4DOF pick and place robot.

关键词： Agriculture robot edge detection robot vision visual servoing

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Age & Gender Recognition Using Deep Learning 3

Age & Gender Recognition Using Deep Learning

引用

3rd international conference on Intelligent Computing, Instrumentation and Control Technologies, ICICICT 2022

作者： Arshin Rizwana, S. Viji Rajendran, V. Nss College of Engineering Department of Computer Science Palakkad India

ISBN: (数字)9781665410052

ISBN: (纸本)9781665410052

Human face image analysis is an important area of research in the science of computer vision. The human face conveys a wealth of information about their particular qualities. One of the most essential challenges in computer vision is recognising a person's gender and age from a facial picture. The most significant characteristics derived from human faces are the eyes, nose, mouth, brows, and so on. These characteristics are employed in a variety of Human-computer Interaction sectors, including security systems, judicial systems, transportation, medical, and many more. The first stage of age and gender recognition is detecting face from the inputted image. There are different techniques for face detection. The next stage is pre-processing where cropping and resizing of image for fast processing the last stage is feature extraction and classification by using deep convolution network. The various methods involved in these stages are studied and from the study building an Age and Gender Recognition System using deep learning. © 2022 IEEE.

关键词： Face recognition

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SEGMENTATION OF OPTICAL-FLOW AND 3D DATA FOR THE INTERPRETATION OF MOBILE OBJECTS

引用

3rd international CONF ON computer vision

作者： MEYGRET, A THONNAT, M INRIA Sophia Antipolis Valbonne France

ISBN: (纸本)0818620579

The detection of mobile 3-D objects using both stereovision and motion information is considered. First, the authors present an optical flow estimation method based on a multiresolution technique for the matching of contour chain points. Then an algorithm of segmentation of the chains using the continuity of the gradient of the apparent velocity is described. A similar algorithm is developed for stereo vision: the segmentation of the chains is performed in function of their 2-D proximity and the continuity of their disparity. These two segmentations are then used to interpret the scene in terms of isolated rigid or deformable objects. Results are shown for two complex real road scenes.

关键词： image processing

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