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共 4643 条记录，以下是771-780 订阅

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Graph Grouping Loss for Metric Learning of Face image Representations

Graph Grouping Loss for Metric Learning of Face Image Repres...

引用

IEEE International conference on visual communications and image processing (VCIP)

作者： Inoue, Nakamasa Tokyo Inst Technol Tokyo Japan

ISBN: (纸本)9781728180687

This paper proposes Graph Grouping (GG) loss for metric learning and its application to face verification. GG loss predisposes image embeddings of the same identity to be close to each other, and those of different identities to be far from each other by constructing and optimizing graphs representing the relation between images. Further, to reduce the computational cost, we propose an efficient way to compute GG loss for cases where embeddings are L-2 normalized. In experiments, we demonstrate the effectiveness o(f) the proposed method for face verification on the VoxCeleb dataset. The results show that the proposed GG loss outperforms conventional losses for metric learning.

关键词： Face recognition

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A Vision Based Fish processing System

A Vision Based Fish Processing System

引用

IEEE International conference on visual communications and image processing (VCIP)

作者： Zhang, Zongjian Yu, Litao Zhang, Jian Wu, Qiang Univ Technol Sydney Sydney NSW Australia

ISBN: (纸本)9781728180687

The digital fish provenance and quality tracking system is essential for the seafood supply chain. As a part of this system, we develop a vision-based fish processing system to automatically perform fish freshness estimation, size measurement and species classification. Under the constrained illumination environment, our system is able to auto-process the fish selection, thus greatly reduce the human labour and bring trust and efficiency to the seafood supply chain from catch to market.

关键词： Fish

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Blood Volume Pulse Signal Extraction based on Spatio-Temporal Low-Rank Approximation for Heart Rate Estimation

Blood Volume Pulse Signal Extraction based on Spatio-Tempora...

引用

IEEE visual communications and image processing (VCIP)

作者： Kosuke Kurihara Yoshihiro Maeda Daisuke Sugimura Takayuki Hamamoto Tokyo University of Science Tokyo Japan Tsuda University Tokyo Japan

ISBN: (纸本)9781665475938

We propose a novel blood volume pulse (BVP) signal extraction method for heart rate estimation that incorporates the self-similarity properties of BVP in the spatial and temporal domains. The main novelty of the proposed method is the incorporation of the temporal self-similarity of BVP via low-rank approximation in the time-delay coordinate system for BVP signal extraction. To make a low-rank approximation of BVP in the time domain, we introduce knowledge of linear time-invariant systems, i.e., the autoregressive (AR) model lies in the low-rank subspace in the time-delay coordinate system. In the medical field, it is widely known that BVP has quasi-periodic temporal characteristics owing to the cardiac pulse and exhibits self-similarity properties in the temporal domain. Hence, we model the temporal behavior of BVP as an AR process, allowing for a low-rank approximation of BVP in the time-delay coordinate system. Low-rank approximation of BVP in the time and spatial domains enables reliable BVP signal extraction, resulting in accurate heart rate estimation. The experiments demonstrate the effectiveness of the proposed method.

关键词： Heart rate visual communication image processing Estimation Behavioral sciences Sensors Reliability

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STSI: Efficiently Mine Spatio- Temporal Semantic Information between Different Multimodal for Video Captioning

STSI: Efficiently Mine Spatio- Temporal Semantic Information...

引用

IEEE visual communications and image processing (VCIP)

作者： Huiyu Xiong Lanxiao Wang School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9781665475938

As one of the challenging tasks in computer vision, video captioning needs to use natural language to describe the content of video. Video contains complex information, such as semantic information, time information and so on. How to synthesize sentences effectively from rich and different kinds of information is very significant. The existing methods often cannot well integrate the multimodal feature to predict the association between different objects in video. In this paper, we improve the existing encoder-decoder structure and propose a network deeply mining the spatio-temporal correlation between multimodal features. Through the analysis of sentence components, we use spatio-temporal semantic information mining module to fuse the object, 2D and 3D features in both time and space. It is worth mentioning that the word output at the previous time is added as the prediction branch of auxiliary conjunctions. After that, a dynamic gumbel scorer is used to output caption sentences that are more consistent with the facts. The experimental results on two benchmark datasets show that our STSI is superior to the state-of-the-art methods while generating more reasonable and semantic-logical sentences.

关键词： visualization Three-dimensional displays Correlation visual communication Fuses image processing Semantics

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CNN-Based Circular Economy in E-Waste Management with Blockchain and IoT Integration

CNN-Based Circular Economy in E-Waste Management with Blockc...

引用

visual Analytics and Data visualization (ICVADV), International conference on

作者： P. Santhuja A Suresh Department of Networking and Communications School of Computing SRM Institute of Science and Technology Chennai Tamil Nadu India Department of Networking and Communications Faculty of Engineering and Technology School of Computing SRM Institute of Science and Technology Chennai Tamil Nadu

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521400

Increasing electronic waste (e-waste) is a serious environmental and financial problem that calls for creative ideas for effective resource recovery and recycling. This paper proposes an IoT- and Blockchain-integrated e-waste management system based on Convolutional Neural Networks (CNNs) to boost automated waste classification and, thus, circular economy practices. While Blockchain guarantees open and safe tracking of waste transportation, IoT sensors and RFID tags allow real-time monitoring of e-waste. Training on a collection of 50,000 e-waste images, a CNN-based image classification model attained an accuracy of 96.2% in classifying components into recyclables, reusables, and hazardous items. Using automated decision-making, the system showed a 28% reduction in processing time and a 32% gain in sorting efficiency over conventional approaches. Blockchain incorporation enhanced traceability through 100% secure transaction records, lowering fraud and illegal disposal. Experimental data show that this method improves 23% resource recovery rates by promoting sustainable e-waste management. The proposed architecture minimizes environmental effects by encouraging ethical e-waste disposal and a closed-loop recycling system. These results show how Blockchain-secured, AI-driven IoT devices might help to advance circular economic ideas for world e-waste management.

关键词： Waste management Training Accuracy Electronic waste Real-time systems Recycling Blockchains Internet of Things Convolutional neural networks Sorting

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CNN-Based Circular Economy in E-Waste Management with Blockchain and IoT Integration

CNN-Based Circular Economy in E-Waste Management with Blockc...

引用

2025 International conference on visual Analytics and Data visualization, ICVADV 2025

作者： Santhuja, P. Suresh, A. School of Computing Srm Institute of Science and Technology Department of Networking and Communications Tamil Nadu Chennai India School of Computing Srm Institute of Science and Technology Faculty of Engineering and Technology Department of Networking and Communications Tamil Nadu Chennai India

ISBN: (纸本)9798331521394

关键词： Electronic Waste

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A Large-scale Sports Tracking Dataset and Progressive Re-detection Based Sports Tracking

A Large-scale Sports Tracking Dataset and Progressive Re-det...

引用

IEEE visual communications and image processing (VCIP)

作者： Han Wang Xiaojun Zhou Qinyu Xu Huaqiang Ren Rong Xie Li Song Shanghai Jiao Tong University MIGU Co. Ltd

ISBN: (纸本)9781665475938

Recent years have witnessed the great progress of visual Object Tracking (VOT) which aims to predict the position of an object in each video frame given only its initial appearance. However, even the state-of-the-art methods are confronted with performance degradation, i.e., the tracker drift problem, in sports video scenes (e.g., soccer, basketball). There are two main causes that should be responsible for the tracker drift problem. First, the object of interest is often occluded by other objects that share a similar appearance. Such severe occlusion prevents the model from distinguishing the correct tracking object from other distractors in the future frames. Second, in sports videos, the objects often move fast from one place to another, which incurs severe blurry visual effects among consecutive frames. To address the issues of the tracker drift problem, we treat VOT as a tracking-by-re-detection task. Specifically, we detect candidate objects within a searching area (determined by object location in the previous frame) in the current frame and develop a progressive algorithm to filter out distractors in the area, which proves robust towards occlusion scenarios and tracker drift problems. Combining the advantages of our settings, the proposed framework method is robust to motion blur and object occlusion issues and achieves state-of-the-art tracking results on our challenging dataset.

关键词： visual communication image processing Manuals Filtering algorithms visual effects Search problems Object tracking

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ICCSPA 2020 - 4th International conference on communications, Signal processing, and their Applications

ICCSPA 2020 - 4th International Conference on Communications...

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4th International conference on communications, Signal processing, and their Applications, ICCSPA 2020

ISBN: (纸本)9781728165356

The proceedings contain 54 papers. The topics discussed include: visual heading estimation for UAVs in indoor environments;fog node optimum placement and configuration technique for VANETs;IoT security in healthcare using AI: a survey;mass flow meter and vehicle information DR land vehicles navigation system in indoor environment;performance analysis of OTFS over multipath channels for visible light communication;polarimetric SAR image denoising using the improved IMMSE filter;DOA estimation in wireless seismic surveys using deep learning;and a succinct review of intelligent computational techniques in green cloud computing.

关键词： Surveys

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RGBD-based Real-time Volumetric Reconstruction System: Architecture Design and Implementation

RGBD-based Real-time Volumetric Reconstruction System: Archi...

引用

IEEE visual communications and image processing (VCIP)

作者： Kai Zhou Shuai Guo Jingchuan Hu Jionghao Wang Qiuwen Wang Li Song Institute of Image Communication and Network Engineering Shanghai Jiao Tong University

ISBN: (纸本)9781665475938

With the increasing popularity of commercial depth cameras, 3D reconstruction of dynamic scenes has aroused widespread interest. Although many novel 3D applications have been unlocked, real-time performance is still a big problem. In this paper, a low-cost, real-time system: LiveRecon3D, is presented, with multiple RGB-D cameras connected to one single computer. The goal of the system is to provide an interactive frame rate for 3D content capture and rendering at a reduced cost. In the proposed system, we adopt a scalable volume structure and employ ray casting technique to extract the surface of 3D content. Based on a pipeline design, all the modules in the system run in parallel and are designed to minimize the latency to achieve an interactive frame rate of 30 FPS. At last, experimental results corresponding to implementation with three Kinect v2 cameras are presented to verify the system's effectiveness in terms of visual quality and real-time performance.

关键词： visualization Three-dimensional displays Costs visual communication Pipelines Systems architecture Cameras

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Cross-Layer Feature based Multi-Granularity visual Classification

Cross-Layer Feature based Multi-Granularity Visual Classific...

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IEEE visual communications and image processing (VCIP)

作者： Junhan Chen Dongliang Chang Jiyang Xie Ruoyi Du Zhanyu Ma Pattern Recognition and Intelligent System Lab. Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781665475938

In contrast to traditional fine-grained visual clas-sification, multi-granularity visual classification is no longer limited to identifying the different sub-classes belonging to the same super-class (e.g., bird species, cars, and aircraft models). Instead, it gives a sequence of labels from coarse to fine (e.g., Passeriformes → Corvidae → Fish Crow), which is more convenient in practice. The key to solving this task is how to use the relationships between the different levels of labels to learn feature representations that contain different levels of granularity. Interestingly, the feature pyramid structure naturally implies different granularity of feature representation, with the shallow layers representing coarse-grained features and the deep layers representing fine-grained features. Therefore, in this paper, we exploit this property of the feature pyramid structure to decouple features and obtain feature representations corre-sponding to different granularities. Specifically, we use shallow features for coarse-grained classification and deep features for fine-grained classification. In addition, to enable fine-grained features to enhance the coarse-grained classification, we propose a feature reinforcement module based on the feature pyramid structure, where deep features are first upsampled and then combined with shallow features to make decisions. Experimental results on three widely used fine-grained image classification datasets such as CUB-200-2011, Stanford Cars, and FGVC-Aircraft validate the method's effectiveness. Code available at https://***/PRIS-CV/CGVC.

关键词： visualization Cross layer design Codes visual communication image processing Fish Birds

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