Suchergebnisse - low-level computer vision and image processing algorithms

ASSERT: A Physician-in-the-Loop Content-Based Retrieval System for HRCT Image Databases von Shyu, Chi-Ren, Brodley, Carla E., Kak, Avinash C., Kosaka, Akio, Aisen, Alex M., Broderick, Lynn S.

“… It is now recognized in many domains that content-based image retrieval from a database of images cannot be carried out by using completely automated approaches …”
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Gradient-Based Camera Exposure Control for Outdoor Mobile Platforms von Shim, Inwook, Oh, Tae-Hyun, Lee, Joon-Young, Choi, Jinwook, Choi, Dong-Geol, Kweon, In So

“… Because most image processing algorithms rely heavily on low-level image features that are based mainly on local gradient information, we consider that gradient quantity can determine the proper …”
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Multi-task vision transformer using low-level chest X-ray feature corpus for COVID-19 diagnosis and severity quantification von Park, Sangjoon, Kim, Gwanghyun, Oh, Yujin, Seo, Joon Beom, Lee, Sang Min, Kim, Jin Hwan, Moon, Sungjun, Lim, Jae-Kwang, Ye, Jong Chul

“… •Backbone with pre-built large CXR dataset is less prone to overfitting.•A multi-task Vision Transformer leveraging low-level features from the backbone was devised …”
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VAE-CoGAN: Unpaired image-to-image translation for low-level vision von Zhang, Juan, Lang, Xiaoqi, Huang, Bo, Jiang, Xiaoyan

“… Low-level vision problems, such as single image haze removal and single image rain removal, usually restore a clear image from an input image using a paired dataset …”
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Unprocessing Images for Learned Raw Denoising von Brooks, Tim, Mildenhall, Ben, Xue, Tianfan, Chen, Jiawen, Sharlet, Dillon, Barron, Jonathan T.

“… This holds true for learned single-image denoising algorithms, which are applied to real raw camera sensor readings but, due to practical constraints, are often trained on synthetic image data …”
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Weighted Nuclear Norm Minimization and Its Applications to Low Level Vision von Gu, Shuhang, Xie, Qi, Meng, Deyu, Zuo, Wangmeng, Feng, Xiangchu, Zhang, Lei

“… As a convex relaxation of the rank minimization model, the nuclear norm minimization (NNM) problem has been attracting significant research interest in recent …”
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Multispectral and Hyperspectral Image Fusion by MS/HS Fusion Net von Xie, Qi, Zhou, Minghao, Zhao, Qian, Meng, Deyu, Zuo, Wangmeng, Xu, Zongben

“… Hyperspectral imaging can help better understand the characteristics of different materials, compared with traditional image systems …”
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Improving Single-Image Defocus Deblurring: How Dual-Pixel Images Help Through Multi-Task Learning von Abuolaim, Abdullah, Afifi, Mahmoud, Brown, Michael S.

“… We are interested in the latter task of defocus deblurring. In particular, we propose a single-image deblurring network that incorporates the two sub-aperture views into a multitask framework …”
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Boosting image denoising effect via low-level noise injection von Xiao, Jian, Cheng, Xiaohui, Xu, Shaoping, Tao, Wuyong, Xiao, Yanyang

“… Adding low-level noise to a preprocessed image can approximate the intensities of some pixels to their original …”
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Adaptive Unfolding Total Variation Network for Low-Light Image Enhancement von Zheng, Chuanjun, Shi, Daming, Shi, Wentian

“… When it comes to sRGB color space, the noise estimation becomes more complicated due to the effect of the image processing pipeline …”
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Faster nonconvex low-rank matrix learning for image low-level and high-level vision: A unified framework von Zhang, Hengmin, Yang, Jian, Qian, Jianjun, Gong, Chen, Ning, Xin, Zha, Zhiyuan, Wen, Bihan

“… This study introduces a unified approach to tackle challenges in both low-level and high-level vision tasks for image processing …”
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Learning to Discover a Unified Architecture for Low-Level Vision von Liu, Zhu, Ma, Long, Liu, Risheng, Fan, Xin

“… (Cross-DARTS for short) framework to discover a unified architecture for different low-level vision tasks automatically, to further widen the capacity of NAS …”
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FOLD: Low-Level Image Enhancement for Low-Light Object Detection Based on FPGA MPSoC von Li, Xiang, Li, Zeyu, Zhou, Lirong, Huang, Zhao

“… , and proposes low-level image enhancement for low-light object detection based on the FPGA MPSoC method …”
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SYENet: A Simple Yet Effective Network for Multiple Low-Level Vision Tasks with Real-time Performance on Mobile Device von Gou, Weiran, Yi, Ziyao, Xiang, Yan, Li, Shaoqing, Liu, Zibin, Kong, Dehui, Xu, Ke

“… With the rapid development of AI hardware accelerators, applying deep learning-based algorithms to solve various low-level vision tasks on mobile devices has gradually become possible …”
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A general framework for low level vision von Sochen, N., Kimmel, R., Malladi, R.

“… We introduce a new geometrical framework based on which natural flows for image scale space and enhancement are presented …”
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AI-based detection and identification of low-level nuclear waste: a comparative analysis von Duani Rojas, Aris, Lagos, Leonel, Upadhyay, Himanshu, Soni, Jayesh, Prabakar, Nagarajan

“… (LLW). Unlike existing methods that rely on human effort, this paper explores the integration of computer vision algorithms to automate the identification of such waste across DOE facilities …”
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Weighted Schatten p -Norm Minimization for Image Denoising and Background Subtraction von Xie, Yuan, Gu, Shuhang, Liu, Yan, Zuo, Wangmeng, Zhang, Wensheng, Zhang, Lei

“… Low rank matrix approximation (LRMA), which aims to recover the underlying low rank matrix from its degraded observation, has a wide range of applications in computer vision …”
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Benchmarking Low-Light Image Enhancement and Beyond von Liu, Jiaying, Xu, Dejia, Yang, Wenhan, Fan, Minhao, Huang, Haofeng

“… the potential of joint optimization of high-level and low-level vision enhancement. To this end, we first propose a large-scale low-light image dataset serving both low/high …”
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Low-Level Spatiochromatic Grouping for Saliency Estimation von Murray, N., Vanrell, M., Otazu, X., Parraga, C. A.

“… In so doing, we hypothesize that the low-level visual mechanisms that enhance or suppress image detail are also responsible for making some image regions more salient …”
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Aggressive and robust low-level control and trajectory tracking for quadrotors with deep reinforcement learning von Chen, Shiyu, Li, Yanjie, Lou, Yunjiang, Lin, Ke

“… Executing accurate trajectory tracking tasks using a high-performance low-level controller is crucial for quadrotors to be applied in various scenarios, especially those involving uncertain disturbances …”
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