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检索条件"任意字段=International Conference on Computer Vision and Image Processing, CVIP 2016"

共 1407 条记录，以下是361-370 订阅

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Point Cloud Mapping Measurements using Kinect RGB-D Sensor and Kinect Fusion for Visual Odometry 12

Point Cloud Mapping Measurements using Kinect RGB-D Sensor a...

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12th international conference on Communication Networks (ICCN) / 12th international conference on Data Mining and Warehousing (ICDMW) / 12th international conference on image and Signal processing (ICISP)

作者： Namitha, N. Vaitheeswaran, S. M. Jayasree, V. K. Bharat, M. K. Coll Engn Alappuzha Dt 688541 Kerala India Natl Aerosp Lab Bengaluru India

RGB-D camera like Kinect make available RGB images along with per-pixel depth information in real time. This paper uses the Kinect Fusion developed by Microsoft Research for the 3D reconstruction of the scene in real time using the MicroKinect Camera and applies it as an aid for Visual Odometry of a Robotic Vehicle where no external reference like GPS is available. (C) 2016 The Authors. Published by Elsevier B.V.

关键词： Kinect Kinect Fusion Odometry Robotics vision

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A Transformer-Based U-Net Architecture for Fast and Efficient image Demoireing 7th

A Transformer-Based U-Net Architecture for Fast and Efficien...

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7th international conference on computer vision and image processing, cvip 2022

作者： Puthussery, Densen Hrishikesh, P.S. Jiji, C.V. Founding Minds Software Trivandrum India SRM University-AP Andhra Pradesh Amaravati India

ISBN: (纸本)9783031314162

Recently, transformer based deep neural networks have been found useful in solving various image restoration tasks like image denoising, deblurring, deraining etc., producing significant improvement in PSNR and SSIM over CNN based techniques on benchmark datasets. These networks have effectively addressed quadratic computational complexity issue with increasing image resolution by making use of novel self attention strategies on local image windows. In this paper, we propose a fast and efficient UNet based architecture using transformer modules for the image demoireing task. The proposed architecture is computationally very efficient as the transformer blocks perform non-overlapping window-based self-attention instead of global self attention. We further improve upon the computational complexity by using decreasing window sizes across scales under the proposed U-Net multi resolution framework. To the best of our knowledge, ours is the first deep network architecture using transformer blocks for the image demoireing problem producing comparable results with state of the art techniques both visually and quantitatively on the CFAMoire challenge dataset [23]. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Restoration

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computer vision Based Fruit Grading System for Quality Evaluation of Tomato in Agriculture industry 7

Computer Vision Based Fruit Grading System for Quality Evalu...

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7th international conference on Communication, Computing and Virtualization (ICCCV)

作者： Arakeria, Megha P. Lakshmana MS Ramaiah Inst Technol Bangalore Karnataka India Sambhram Inst Technol Bangalore Karnataka India

Agriculture sector plays a key role in the economic development of India. The task of fruit grading is vital in the agricultural industry because there is a great demand for high quality fruits in the market. However, fruit grading by human is inefficient, labor intensive and prone to error. The automated grading system not only speeds up the time of processing, but also minimizes error. There is a great demand for tomatoes in both local and foreign markets. The tomato fruit is very delicate and hence careful handling of this fruit is required during grading. Thus, this paper proposes an automatic and effective tomato fruit grading system based on computer vision techniques. The proposed quality evaluation method consists of two phases: development of hardware and software. The hardware is developed to capture the image of the tomato and move the fruit to the appropriate bins without manual intervention. The software is developed using image processing techniques to analyze the fruit for defects and ripeness. Experiments were carried out on several images of the tomato fruit. It was observed that the proposed method was successful with 96.47% accuracy in evaluating the quality of the tomato. (C) 2016 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the Organizing Committee of ICCCV 2016

关键词： computer vision Tomato Defect Ripeness Agriculture

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Human activity recognition in ambient assisted living for Alzheimer's patient: A review of trends and challenges in Malaysia

Human activity recognition in ambient assisted living for Al...

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2016 international conference on Interfaces and Human computer Interaction, IHCI 2016, Game and Entertainment Technologies, GET 2016 and computer Graphics, Visualization, computer vision and image processing, CGVcvip 2016

作者： Basharudin, Nur Waheeda Azir, Ku Nurul Fazira Ku School of Computer and Communication Engineering Universiti Malaysia Perlis Perlis Malaysia

ISBN: (纸本)9789898533524

Human activity recognition is one of the method to model human behaviors and activity patterns. The works have becoming a significant research interest in recent years for various applications such as for assisted living and healthcare. This paper will reviews some of the related works based on stochastic methods or well known as probabilistic method to classify human activities which are focusing on kitchen activity. However, many challenging issues need to be reviewed in order to design and implement these technologies. The main purpose of this review is to extensively identify the existing method and characterize the literature in a manner that brings key challenges of future probabilistic method to meet the demand of cultures and social of Alzheimer's patient in Malaysia.

关键词： Assisted living

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Real-time image scanning framework using GPGPU – Face detection case study

Real-time image scanning framework using GPGPU – Face detec...

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2016 international conference on image processing, computer vision, and Pattern Recognition, IPCV 2016

作者： Fayez, Mahmoud Faheem, H.M. Katib, Iyad Aljohani, Naif Radi Faculty of Computer and Information Science Ain Shams University Egypt Fujitsu Japan Faculty of Computing and Information Technology King Abdulaziz University Saudi Arabia

ISBN: (纸本)1601324421

—The image scanning problem has been tackled several times from different research perspectives. Speeding up image scanning is a major factor in significantly reducing the time needed to perform face detection operations. In this paper, we introduce a novel framework that easily allows the user to define the scaling factor and the scanning window displacement. The proposed framework deploys the NVIDIA GPGPU in a very efficient way by sorting the working threads to achieve the highest memory throughput. A face detection case study using the Viola-Jones algorithm has been investigated. Results show an increase in frames processed per second, approaching 37 fps for HD images. © CSREA Press.

关键词： Face recognition

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Skin Disease Detection Using Saliency Maps and Segmentation Techniques 7th

Skin Disease Detection Using Saliency Maps and Segmentation ...

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7th international conference on computer vision and image processing, cvip 2022

作者： Toteja, Rishit Gupta, Dhruv Gautam, Vibhor Vishwakarma, Dinesh Kumar Delhi Technological University Shahbad Daulatpur Main Bawana Road Delhi110042 India

ISBN: (纸本)9783031314063

Skin diseases are the most common disease on the planet. When detecting skin diseases, dermatologists must have a high degree of expertise and precision, which is why computer-aided diagnosis is so helpful. An approach for detecting skin diseases has been presented to give more information. Several investigations have been carried out to aid in diagnosing skin disorders such as skin cancer and skin tumours. However, exact identification of skin disease is challenging to cure because of the following factors: visual likeness, little contrast in-between the lesions and skin that is between the affected and non-diseased areas, etc. In this paper we propose a model that uses an image set which is pre-processed by various techniques like deblurring, noise reduction, and then enhanced. The images are then segmented using U-Net and MobileNetV2 is used for classification. The disease is detected at the output for a corresponding input image based on the definite pattern pertaining to a dispersant in the processed image. Then, we compute a class saliency map for the provided image and class. We demonstrate how ConvNets may classify and segment skin diseases using such maps. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： image segmentation

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T2CI-GAN: Text to Compressed image Generation Using Generative Adversarial Network 7th

T2CI-GAN: Text to Compressed Image Generation Using Generati...

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7th international conference on computer vision and image processing, cvip 2022

作者： Rajesh, Bulla Dusa, Nandakishore Javed, Mohammed Dubey, Shiv Ram Nagabhushan, P. Department of IT IIIT Allahabad U.P Prayagraj211015 India Department of CSE Vignan University A.P Guntur522213 India

ISBN: (纸本)9783031314162

The problem of generating textual descriptions for the visual data has gained research attention in the recent years. In contrast to that the problem of generating visual data from textual descriptions is still very challenging, because it requires the combination of both Natural Language processing (NLP) and computer vision techniques. The existing methods utilize the Generative Adversarial Networks (GANs) and generate the uncompressed images from textual description. However, in practice, most of the visual data are processed and transmitted in the compressed representation. Hence, the proposed work attempts to generate the visual data directly in the compressed representation form using Deep Convolutional GANs (DCGANs) to achieve the storage and computational efficiency. We propose GAN models for compressed image generation from text. The first model is directly trained with JPEG compressed DCT images (compressed domain) to generate the compressed images from text descriptions. The second model is trained with RGB images (pixel domain) to generate JPEG compressed DCT representation from text descriptions. The proposed models are tested on an open source benchmark dataset Oxford-102 Flower images using both RGB and JPEG compressed versions, and accomplished the state-of-the-art performance in the JPEG compressed domain. The code will be publicly released at GitHub after acceptance of paper. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Generative adversarial networks

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Measurement of the Zone of Inhibition of an Antibiotic 6

Measurement of the Zone of Inhibition of an Antibiotic

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IEEE 6th international Advance Computing conference (IACC)

作者： Bhargav, H. S. Shastri, Sachin D. Poornav, S. P. Darshan, K. M. Nayak, Mahendra M. PES Inst Technol Dept Comp Sci & Engn Bangalore Karnataka India PES Inst Technol Dept Informat Sci & Engn Bangalore Karnataka India PES Inst Technol Dept Elect & Elect Engn Bangalore Karnataka India

ISBN: (纸本)9781467382861

In the Disk Diffusion Antibiotic Sensitivity test (The Kirby-Bauer test) a thin film of bacteria applied on a plate is subjected to various antibiotics. The Zone of inhibition is a circular area around the spot of the antibiotic in which the bacteria colonies do not grow. The zone of inhibition can be used to measure the susceptibility of the bacteria to wards the antibiotic. The process of measuring the diameter of this Zone of Inhibition can be automated using image processing. In this work an algorithm is developed, using computer vision, which will detect the zones of inhibition of the bacteria. This work demonstrates an effective approach of measuring the Zone of Inhibition by calculating the radius of the zone by drawing contours and setting the right value of threshold. This work also determines if a particular bacteria is susceptible or resistant to the applied antibiotic using the calculated Zone of Inhibition and the prescribed standard values.

关键词： Biomedical image processing computer vision

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vision HELPER: CNN Based Real Time Navigator for the Visually Impaired 6th

VISION HELPER: CNN Based Real Time Navigator for the Visua...

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6th international conference on computer vision and image processing, cvip 2021

作者： Maheshwari, Chetan Kumar, Pawan Gupta, Ajeet Bandyopadhyay, Oishila Indian Institute of Information Technology Kalyani West Bengal Kalyani India

ISBN: (纸本)9783031113451

Visually impaired persons often face difficulty to move around in new environment, especially on road. Information about the presence of different objects in his/her surroundings can help the person to move independently. This work focuses on development of a Convolution Neural Network (CNN) based portable assistive system for visually impaired people. The system will provide real-time auditory description of the object appearing in the visually challenged person’s way along with its relative location. This assists the person to move independently inside house and workplace or on streets. The proposed system will capture real-time video through the camera of the android mobile set of the user (visually challenged person). The video input will be processed by trained CNN model and the object classification result will be used to compute the relative location of the object and to generate the warning for collision in form of auditory description for the user. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Convolutional neural networks

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Domain Adaptation Based Technique for image Emotion Recognition Using image Captions 5th

Domain Adaptation Based Technique for Image Emotion Recognit...

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5th international conference on computer vision and image processing, cvip 2020

作者： Kumar, Puneet Raman, Balasubramanian Department of Computer Science and Engineering Indian Institute of Technology Roorkee Roorkee India

ISBN: (纸本)9789811610912

images are powerful tools for affective content analysis. image emotion recognition is useful for graphics, gaming, animation, entertainment, and cinematography. In this paper, a technique for recognizing the emotions in images containing facial, non-facial, and non-human components has been proposed. The emotion-labeled images are mapped to their corresponding textual captions. Then the captions are used to re-train a text emotion recognition model as the domain-adaptation approach. The adapted text emotion recognition model has been used to classify the captions into discrete emotion classes. As image captions have a one-to-one mapping with the images, the emotion labels predicted for the captions have been considered the emotion labels of the images. The suitability of using the image captions for emotion classification has been evaluated using caption-evaluation metrics. The proposed approach serves as an example to address the unavailability of sufficient emotion-labeled image datasets and pre-trained models. It has demonstrated an accuracy of 59.17% for image emotion recognition. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Emotion Recognition

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