检索结果-内蒙古大学图书馆

IEEE Transactions on Audio, Speech and Language processing 2025年 33卷 2045-2058页

作者： Yiming Zhang Xuenan Xu Ruoyi Du Haohe Liu Yuan Dong Zheng-Hua Tan Wenwu Wang Zhanyu Ma Pattern Recognition and Intelligent System Laboratory School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing China Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China Centre for Vision Speech and Signal Processing University of Surrey Guildford U.K. Department of Electronic Systems Aalborg University Aalborg Denmark

In traditional audio captioning methods, a model is usually trained in a fully supervised manner using a human-annotated dataset containing audio-text pairs and then evaluated on the test set from the same dataset. Such methods have two limitations. First, these methods are often data-hungry and require time-consuming and expensive human annotations to obtain audio-text pairs. Second, these models often suffer from performance degradation in cross-domain scenarios, i.e., when the input audio comes from a different domain than the training set, and this issue has received little attention. To address these issues, we propose a new zero-shot method for audio captioning. Our method is built on the contrastive language-audio pre-training (CLAP) model. During training, the model reconstructs the ground-truth caption using the CLAP text encoder. In the inference stage, the model generates text descriptions from the CLAP audio embeddings of given audio inputs. To enhance the ability of the model in transitioning from text-to-text generation to audio-to-text generation, we propose to use the mixed-augmentations-based soft prompt to learn more robust latent representations, leveraging instance replacement and embedding augmentation. Additionally, we introduce the retrieval-based acoustic-aware hard prompt to improve the cross-domain performance of the model by employing the domain-agnostic label information of sound events. Extensive experiments on AudioCaps and Clotho benchmarks show the effectiveness of our proposed method, which outperforms other zero-shot audio captioning approaches for in-domain scenarios and outperforms the compared methods for cross-domain scenarios, underscoring the generalization ability of our method.

关键词： Training Decoding Semantics Data models Acoustics electronic mail Benchmark testing Transformers Robustness Perturbation methods

来源：评论

学校读者我要写书评

暂无评论

Deep Learning in Palmprint Recognition-A Comprehensive Survey

arXiv

引用

arXiv 2025年

作者： Gao, Chengrui Yang, Ziyuan Jia, Wei Leng, Lu Zhang, Bob Teoh, Andrew Beng Jin College of Computer Science Sichuan University Chengdu610065 China Singapore School of Computer and Information Hefei University of Technology Hefei China Jiangxi Provincial Key Laboratory of Image Processing and Pattern Recognition Nanchang Hangkong University Nanchang China Pattern Analysis and Machine Intelligence Group Department of Computer and Information Science University of Macau Taipa China School of Electrical and Electronic Engineering College of Engineering Yonsei University Seoul Korea Republic of

Palmprint recognition has emerged as a prominent biometric technology, widely applied in diverse scenarios. Traditional handcrafted methods for palmprint recognition often fall short in representation capability, as they heavily depend on researchers' prior knowledge. Deep learning (DL) has been introduced to address this limitation, leveraging its remarkable successes across various domains. While existing surveys focus narrowly on specific tasks within palmprint recognition-often grounded in traditional methodologies-there remains a significant gap in comprehensive research exploring DL-based approaches across all facets of palmprint recognition. This paper bridges that gap by thoroughly reviewing recent advancements in DL-powered palmprint recognition. The paper systematically examines progress across key tasks, including region-of-interest segmentation, feature extraction, and security/privacy-oriented challenges. Beyond highlighting these advancements, the paper identifies current challenges and uncovers promising opportunities for future research. By consolidating state-of-the-art progress, this review serves as a valuable resource for researchers, enabling them to stay abreast of cutting-edge technologies and drive innovation in palmprint recognition. Copyright © 2025, The Authors. All rights reserved.

关键词： Biometrics

来源：评论

学校读者我要写书评

暂无评论

1.5V resistive fuse for image smoothing and segmentation

引用

electronicS LETTERS 1997年第10期33卷 851-852页

作者： Athreya, JKV Gregson, PH Department of Electrical Engineering Computer Vision and Image Processing Laboratory Technical University of Nova Scotia Halifax Canada

A 1.5V resistive fuse for image smoothing and segmentation using bulk-driven MOSFETs is presented. The circuit switches on only if the differential voltage applied across its input terminals is less than a set voltage;it switches off if the differential voltage is higher than the set value. The useful operation range of the circuit is 0.4V with a supply voltage of 1.5V and threshold voltages of V-Tn = 0.828V and V-Tp = -0.56V for n and g channel MOSFETs, respectively.

关键词： image processing segmentation (image processing)

来源：评论

学校读者我要写书评

暂无评论

Texture segmentation using hierarchical wavelet decomposition

引用

PATTERN RECOGNITION 1995年第12期28卷 1819-1824页

作者： Salari, E Ling, Z Computer Vision and Image Processing Laboratory Department of Electrical Engineering University of Toledo Toledo OH 43606 U.S.A.

This paper presents a texture segmentation algorithm based on a hierarchical wavelet decomposition. Using Daubechies' four-tap filter, an original image is decomposed into three detail images and one approximate image. The decomposition can be recursively applied to the approximate image to generate a lower resolution of the pyramid. The segmentation starts at the lowest resolution using the K-means clustering scheme and textural features obtained from various sub-bands. The result of segmentation is propagated through the pyramid to a higher resolution with continuously improving the segmentation. The lower resolution levels help to build the contour of the segmented texture, while higher levels refine the process, and correct possible errors.

关键词： Texture segmentation Wavelet transform Clustering algorithm Multiresolution segmentation

来源：评论

学校读者我要写书评

暂无评论

Channel and space-based joint rate allocation algorithm

Channel and space-based joint rate allocation algorithm

引用

International Conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Dayong Wang Chao Yuan Yu Sun Xin Lu Hui Guo Frederic Dufaux Ce Zhu Key Laboratory of Big Data Intelligent Computing Chongqing University of Posts and Telecommunications Guangxi Key Laboratory of Machine Vision and Intelligent Control Wuzhou University Chongqing Key Laboratory of Image Cognition Chongqing University of Posts and Telecommunications China Department of Computer Science University of Central Arkansas Faculty of Computing Engineering and Media (CEM) De Montfort University UK Université Paris-Saclay CNRS CentraleSupélec Laboratoire Des Signaux et Systèmes France School of Information and Communication Engineering University of Electronic Science and Technology of China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Rate control is a critical component for image and video compression Particularly under limited network bandwidth conditions, bitrate control is essential to ensure efficient image transmission by effectively allocation channel resources. In this research, since both Channel and Spatial have relationship with rate allocation, we first propose a joint Channel-wise and Spatial-wise Quantization scheme to determine optimal quantization parameters. Subsequently, we develop a quantization step estimation network to obtain parameters to efficiently allocate rate according to target rate. Experiments demonstrate that our algorithm significantly improve compressed image quality with minimal bitrate distortion and achieve accurate rate control with nearly 3% average bitrate error.

关键词： image quality Quantization (signal) image coding Bit rate Signal processing algorithms Estimation Rate-distortion Video compression Resource management Speech processing

来源：评论

学校读者我要写书评

暂无评论

ZERO CROSSINGS, BANDWIDTH COMPRESSION, AND RESTORATION OF NONLINEARLY DISTORTED BAND-LIMITED SIGNALS

引用

JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS image SCIENCE AND vision 1986年第5期3卷 651-654页

作者： MARVASTI, F JAIN, AK Computer Vision and Image Processing Laboratory Department of Electrical and Computer Engineering University of California at Davis Davis California 95616 USA

This paper discusses the relationship between the zero crossings or zeros of band-limited signals and their nonlinear transformations. It is proved that the bandwidth of a signal can be compressed by a ratio of 1/ n if and only if the signal has n th-order zero crossings or zeros (if complex). Also, a monotonic nonlinearity in the observation of a band-limited signal can be identified from the zero crossings (or zeros) of the derivative of the observed signal. (The results are for one-dimensional signals. Extensions to two-dimensional signals remain to be addressed.)

关键词： Coherent systems Distortion electronic imaging Imaging systems Modulation Phase shift

来源：评论

学校读者我要写书评

暂无评论

Two-stage neural network for volume segmentation of medical images

Two-stage neural network for volume segmentation of medical ...

引用

1997 IEEE International Conference on Neural Networks (ICNN 97)

作者： Ahmed, MN Farag, AA Computer Vision and Image Processing Laboratory University of Louisville Department of Electrical Engineering Louisville KY 40292 United States

ISBN: (纸本)0780341236

In this paper, we present a new system to segment and label CT/MRI Brain slices using feature extraction and unsupervised clustering. In this technique, each voxel is assigned a feature pattern consisting of a scaled family of differential geometrical invariant features. The invariant feature pattern is then assigned to a specific region using a two-stage neural network system. The first stage is a self-organizing principal components analysis (SOPCA) network that is used to project the feature vector onto its leading principal axes found by using principal components analysis. This step provides an effective basis for feature extraction. The second stage consists of a self-organizing feature map (SOFM) which will automatically cluster the input vector into different regions. The optimum number of regions (clusters) is obtained by a model fitting approach. Finally, a 3D connected component labeling algorithm is applied to ensure region connectivity. Implementation and performance of this technique are presented. Compared to other approaches, the new system is more accurate in extracting 3D anatomical structures of the brain, and can be apdated to real-time imaging scenarios.

关键词： segmentation pattern analysis learning in vision

来源：评论

学校读者我要写书评

暂无评论

Resolving ambiguity in depth extraction for motion capture using genetic algorithm

Resolving ambiguity in depth extraction for motion capture u...

引用

2002 Congress on Evolutionary Computation, CEC 2002

作者： Wai, Yin Yee Chow, Chi Kin Lee, Tong Computer Vision and Image Processing Laboratory Dept. of Electronic Engineering Chinese University of Hong Kong Shatin Hong Kong

ISBN: (纸本)0780372824

There is considerable interest in motion capture from an image sequence taken from a video camera. However, since the images only consist of 2D information, the distance of an object from the image plane cannot be determined uniquely unless some constraints are imposed. Coplanar motion is a popular constraint adopted for this purpose. If the captured motion is not coplanar, only two possible solutions can be obtained at the best even the actual size of the object is given. Therefore, the motion cannot be captured without resolving the distances of each control point from the image plane. By assuming smooth transition, the problem is formulated as one minimizing the transition between image frames and the application of GA to solve this optimization problem is proposed. © 2002 IEEE.

关键词： Video cameras

来源：评论

学校读者我要写书评

暂无评论

Brain MR image segmentation using tabu search and hidden markov random field model

Brain MR image segmentation using tabu search and hidden mar...

引用

2nd Indian International Conference on Artificial Intelligence, IICAI 2005

作者： Nanda, P.K. Patra, D. Pradhan, A. Department of Electrical Engineering Image Processing and Computer Vision Laboratory National Institute of Technology Rourkela Orissa 769008 India

ISBN: (纸本)0972741216

In this paper, we propose a hybrid Tabu Expectation Maximization (TEM) Algorithm for segmentation of Brain Magnetic Resonance (MR) images in both supervised and unsupervised framewrok. Gaussian Hidden Markov Random Field (GHMRF) is used to model the available degraded image. In supervised framework, the apriori image MRF model parameters as well as the GHMRF model parameters are assumed to be known. The class labels are estimated using the Maximum a Posteriori (MAP) estimation criterion. In unsupervised framework, the problem of model parameter estimation and label estimation is formulated in Expectation Maximization (EM) framework. The labels are estimated using the proposed Tabu Search algorithm while the model parameters are the maximum likelihood estimates. Our proposed algorithm yields results with arbitrary initial paramater set and thus overcomes the problem of proper choice of initial parameters. The results obtained are comparable with the results obtained by using the algorithm proposed by Zhang ***. [15] , where the Iterated Conditional Mode (ICJM) algorithm is used for computing the MAP estimates. Copyright © IICAI 2005.

关键词： Tabu search

来源：评论

学校读者我要写书评

暂无评论

Random-valued impulse denoising using a fast l 1-minimization-based image inpainting technique

Random-valued impulse denoising using a fast l 1-minimizatio...

引用

International Conference on Emerging Trends and Advances in Electrical engineering and Renewable Energy, ETAEERE 2016

作者： Kalita, Mayuri Deka, Bhabesh Computer Vision and Image Processing Laboratory Department of Electronics and Communication Engineering Tezpur University TezpurAssam784028 India

ISBN: (纸本)9789811047640

In this chapter, an image inpainting approach based on l 1-norm regularization is presented for the estimation of pixels corrupted by the random-valued impulse noise. It is a two-stage reconstruction scheme. First, a reasonably accurate random-valued impulse detection scheme is applied to detect the corrupted pixels. Next, the corrupted pixels are treated as missing pixels and replaced by using an image inpainting technique. The inpainting method is based on the fast iterative shrinkage thresholding algorithm (FISTA). The proposed method is fast and experimental results show that it is robust to non-Gaussian and nonadditive degradations like the random-valued impulse noise. It also outperforms similar random-valued impulse denoising schemes in terms of computational complexity while preserving the image quality. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Pixels

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：