China Graphics Society (CGS) is a national, academic, and non-profit organization. It’s founded in 1980 and is affiliated to China Association for Science and Technology. CGS gathers a large number of renowned experts, scholars and science and technology in realm of graphics, with a membership of over 100,000 people. CGS is one of the initiators of International Society for Geometry and Graphics (ISGG), and is its group member. CGS has actively assigned delegations to attend the international Conference on Geometry and Graphics (ICGG) held by ISGG and successfully hosted ICGG in China for many times.
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Citation: Visual Computing for Industry, Biomedicine, and Art 2024 7:19
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Revolutionizing anemia detection: integrative machine learning models and advanced attention mechanisms
This study addresses the critical issue of anemia detection using machine learning (ML) techniques. Although a widespread blood disorder with significant health implications, anemia often remains undetected. T...
Citation: Visual Computing for Industry, Biomedicine, and Art 2024 7:18 -
Omni-dimensional dynamic convolution feature coordinate attention network for pneumonia classification
Pneumonia is a serious disease that can be fatal, particularly among children and the elderly. The accuracy of pneumonia diagnosis can be improved by combining artificial-intelligence technology with X-ray ima...
Citation: Visual Computing for Industry, Biomedicine, and Art 2024 7:17 -
Non-invasively identifying candidates of active surveillance for prostate cancer using magnetic resonance imaging radiomics
Active surveillance (AS) is the primary strategy for managing patients with low or favorable-intermediate risk prostate cancer (PCa). Identifying patients who may benefit from AS relies on unpleasant prostate ...
Citation: Visual Computing for Industry, Biomedicine, and Art 2024 7:16 -
Two-step hierarchical binary classification of cancerous skin lesions using transfer learning and the random forest algorithm
Skin lesion classification plays a crucial role in the early detection and diagnosis of various skin conditions. Recent advances in computer-aided diagnostic techniques have been instrumental in timely interve...
Citation: Visual Computing for Industry, Biomedicine, and Art 2024 7:15 -
Parallel processing model for low-dose computed tomography image denoising
Low-dose computed tomography (LDCT) has gained increasing attention owing to its crucial role in reducing radiation exposure in patients. However, LDCT-reconstructed images often suffer from significant noise ...
Citation: Visual Computing for Industry, Biomedicine, and Art 2024 7:14 -
Simulated deep CT characterization of liver metastases with high-resolution filtered back projection reconstruction
Early diagnosis and accurate prognosis of colorectal cancer is critical for determining optimal treatment plans and maximizing patient outcomes, especially as the disease progresses into liver metastases. Comp...
Citation: Visual Computing for Industry, Biomedicine, and Art 2024 7:13 -
Schlieren imaging and video classification of alphabet pronunciations: exploiting phonetic flows for speech recognition and speech therapy
Speech is a highly coordinated process that requires precise control over vocal tract morphology/motion to produce intelligible sounds while simultaneously generating unique exhaled flow patterns. The schliere...
Citation: Visual Computing for Industry, Biomedicine, and Art 2024 7:12 -
V4RIN: visual analysis of regional industry network with domain knowledge
The regional industry network (RIN) is a type of financial network derived from industry networks that possess the capability to describe the connections between specific industries within a particular region....
Citation: Visual Computing for Industry, Biomedicine, and Art 2024 7:11 -
Typicality- and instance-dependent label noise-combating: a novel framework for simulating and combating real-world noisy labels for endoscopic polyp classification
Learning with noisy labels aims to train neural networks with noisy labels. Current models handle instance-independent label noise (IIN) well; however, they fall short with real-world noise. In medical image c...
Citation: Visual Computing for Industry, Biomedicine, and Art 2024 7:10 -
Dual modality prompt learning for visual question-grounded answering in robotic surgery
With recent advancements in robotic surgery, notable strides have been made in visual question answering (VQA). Existing VQA systems typically generate textual answers to questions but fail to indicate the loc...
Citation: Visual Computing for Industry, Biomedicine, and Art 2024 7:9 -
Automated analysis of pectoralis major thickness in pec-fly exercises: evolving from manual measurement to deep learning techniques
This study addresses a limitation of prior research on pectoralis major (PMaj) thickness changes during the pectoralis fly exercise using a wearable ultrasound imaging setup. Although previous studies used man...
Citation: Visual Computing for Industry, Biomedicine, and Art 2024 7:8 -
Three-dimensional reconstruction of industrial parts from a single image
This study proposes an image-based three-dimensional (3D) vector reconstruction of industrial parts that can generate non-uniform rational B-splines (NURBS) surfaces with high fidelity and flexibility. The con...
Citation: Visual Computing for Industry, Biomedicine, and Art 2024 7:7 -
PlaqueNet: deep learning enabled coronary artery plaque segmentation from coronary computed tomography angiography
Cardiovascular disease, primarily caused by atherosclerotic plaque formation, is a significant health concern. The early detection of these plaques is crucial for targeted therapies and reducing the risk of ca...
Citation: Visual Computing for Industry, Biomedicine, and Art 2024 7:6 -
Flipover outperforms dropout in deep learning
Flipover, an enhanced dropout technique, is introduced to improve the robustness of artificial neural networks. In contrast to dropout, which involves randomly removing certain neurons and their connections, f...
Citation: Visual Computing for Industry, Biomedicine, and Art 2024 7:4 -
Correction: Multi-task approach based on combined CNN-transformer for efficient segmentation and classification of breast tumors in ultrasound images
Citation: Visual Computing for Industry, Biomedicine, and Art 2024 7:5 -
Convolutional neural network based data interpretable framework for Alzheimer’s treatment planning
Alzheimer’s disease (AD) is a neurological disorder that predominantly affects the brain. In the coming years, it is expected to spread rapidly, with limited progress in diagnostic techniques. Various machine ...
Citation: Visual Computing for Industry, Biomedicine, and Art 2024 7:3 -
Multi-task approach based on combined CNN-transformer for efficient segmentation and classification of breast tumors in ultrasound images
Nowadays, inspired by the great success of Transformers in Natural Language Processing, many applications of Vision Transformers (ViTs) have been investigated in the field of medical image analysis including b...
Citation: Visual Computing for Industry, Biomedicine, and Art 2024 7:2 -
CT-based radiomics: predicting early outcomes after percutaneous transluminal renal angioplasty in patients with severe atherosclerotic renal artery stenosis
This study aimed to comprehensively evaluate non-contrast computed tomography (CT)-based radiomics for predicting early outcomes in patients with severe atherosclerotic renal artery stenosis (ARAS) after percu...
Citation: Visual Computing for Industry, Biomedicine, and Art 2024 7:1 -
Adaptive feature extraction method for capsule endoscopy images
The traditional feature-extraction method of oriented FAST and rotated BRIEF (ORB) detects image features based on a fixed threshold; however, ORB descriptors do not distinguish features well in capsule endosc...
Citation: Visual Computing for Industry, Biomedicine, and Art 2023 6:24 -
Comprehensive integrated analysis of MR and DCE-MR radiomics models for prognostic prediction in nasopharyngeal carcinoma
Although prognostic prediction of nasopharyngeal carcinoma (NPC) remains a pivotal research area, the role of dynamic contrast-enhanced magnetic resonance (DCE-MR) has been less explored. This study aimed to i...
Citation: Visual Computing for Industry, Biomedicine, and Art 2023 6:23 -
Local imperceptible adversarial attacks against human pose estimation networks
Deep neural networks are vulnerable to attacks from adversarial inputs. Corresponding attack research on human pose estimation (HPE), particularly for body joint detection, has been largely unexplored. Transfe...
Citation: Visual Computing for Industry, Biomedicine, and Art 2023 6:22 -
Reliable knowledge graph fact prediction via reinforcement learning
Knowledge graph (KG) fact prediction aims to complete a KG by determining the truthfulness of predicted triples. Reinforcement learning (RL)-based approaches have been widely used for fact prediction. However,...
Citation: Visual Computing for Industry, Biomedicine, and Art 2023 6:21 -
Application and prospects of AI-based radiomics in ultrasound diagnosis
Artificial intelligence (AI)-based radiomics has attracted considerable research attention in the field of medical imaging, including ultrasound diagnosis. Ultrasound imaging has unique advantages such as high...
Citation: Visual Computing for Industry, Biomedicine, and Art 2023 6:20 -
Focus-RCNet: a lightweight recyclable waste classification algorithm based on focus and knowledge distillation
Waste pollution is a significant environmental problem worldwide. With the continuous improvement in the living standards of the population and increasing richness of the consumption structure, the amount of d...
Citation: Visual Computing for Industry, Biomedicine, and Art 2023 6:19 -
Novel 3D local feature descriptor of point clouds based on spatial voxel homogenization for feature matching
Obtaining a 3D feature description with high descriptiveness and robustness under complicated nuisances is a significant and challenging task in 3D feature matching. This paper proposes a novel feature descrip...
Citation: Visual Computing for Industry, Biomedicine, and Art 2023 6:18 -
Discrimination between leucine-rich glioma-inactivated 1 antibody encephalitis and gamma-aminobutyric acid B receptor antibody encephalitis based on ResNet18
This study aims to discriminate between leucine-rich glioma-inactivated 1 (LGI1) antibody encephalitis and gamma-aminobutyric acid B (GABAB) receptor antibody encephalitis using a convolutional neural network ...
Citation: Visual Computing for Industry, Biomedicine, and Art 2023 6:17 -
Hyperparameter optimization for cardiovascular disease data-driven prognostic system
Prediction and diagnosis of cardiovascular diseases (CVDs) based, among other things, on medical examinations and patient symptoms are the biggest challenges in medicine. About 17.9 million people die from CVD...
Citation: Visual Computing for Industry, Biomedicine, and Art 2023 6:16 -
Survey of methods and principles in three-dimensional reconstruction from two-dimensional medical images
Three-dimensional (3D) reconstruction of human organs has gained attention in recent years due to advances in the Internet and graphics processing units. In the coming years, most patient care will shift towar...
Citation: Visual Computing for Industry, Biomedicine, and Art 2023 6:15 -
Vision transformer architecture and applications in digital health: a tutorial and survey
The vision transformer (ViT) is a state-of-the-art architecture for image recognition tasks that plays an important role in digital health applications. Medical images account for 90% of the data in digital me...
Citation: Visual Computing for Industry, Biomedicine, and Art 2023 6:14 -
DB-DCAFN: dual-branch deformable cross-attention fusion network for bacterial segmentation
Sputum smear tests are critical for the diagnosis of respiratory diseases. Automatic segmentation of bacteria from sputum smear images is important for improving diagnostic efficiency. However, this remains a ...
Citation: Visual Computing for Industry, Biomedicine, and Art 2023 6:13 -
Editorial: advances in deep learning techniques for biomedical imaging
Citation: Visual Computing for Industry, Biomedicine, and Art 2023 6:12 -
Beyond the horizon: immersive developments for animal ecology research
More diverse data on animal ecology are now available. This “data deluge” presents challenges for both biologists and computer scientists; however, it also creates opportunities to improve analysis and answer ...
Citation: Visual Computing for Industry, Biomedicine, and Art 2023 6:11 -
Systematic review of digital twin technology and applications
As one of the most important applications of digitalization, intelligence, and service, the digital twin (DT) breaks through the constraints of time, space, cost, and security on physical entities, expands and...
Citation: Visual Computing for Industry, Biomedicine, and Art 2023 6:10 -
Translating radiology reports into plain language using ChatGPT and GPT-4 with prompt learning: results, limitations, and potential
The large language model called ChatGPT has drawn extensively attention because of its human-like expression and reasoning abilities. In this study, we investigate the feasibility of using ChatGPT in experimen...
Citation: Visual Computing for Industry, Biomedicine, and Art 2023 6:9 -
EM-Gaze: eye context correlation and metric learning for gaze estimation
In recent years, deep learning techniques have been used to estimate gaze—a significant task in computer vision and human-computer interaction. Previous studies have made significant achievements in predicting...
Citation: Visual Computing for Industry, Biomedicine, and Art 2023 6:8 -
Simulation and optimization of scrap wagon dismantling system based on Plant Simulation
Based on the existing plant layout and process flow, a simulation analysis was conducted using the Plant Simulation platform with the utilization efficiency of each station and production capacity of the disma...
Citation: Visual Computing for Industry, Biomedicine, and Art 2023 6:7 -
Defect detection of gear parts in virtual manufacturing
Gears play an important role in virtual manufacturing systems for digital twins; however, the image of gear tooth defects is difficult to acquire owing to its non-convex shape. In this study, a deep learning n...
Citation: Visual Computing for Industry, Biomedicine, and Art 2023 6:6 -
Rendering algorithms for aberrated human vision simulation
Vision-simulated imagery―the process of generating images that mimic the human visual system―is a valuable tool with a wide spectrum of possible applications, including visual acuity measurements, personalized...
Citation: Visual Computing for Industry, Biomedicine, and Art 2023 6:5 -
Robustness optimization for rapid prototyping of functional artifacts based on visualized computing digital twins
This study presents a robustness optimization method for rapid prototyping (RP) of functional artifacts based on visualized computing digital twins (VCDT). A generalized multiobjective robustness optimization ...
Citation: Visual Computing for Industry, Biomedicine, and Art 2023 6:4 -
Preliminary landscape analysis of deep tomographic imaging patents
Over recent years, the importance of the patent literature has become increasingly more recognized in the academic setting. In the context of artificial intelligence, deep learning, and data sciences, patents ...
Citation: Visual Computing for Industry, Biomedicine, and Art 2023 6:3 -
Photon-counting computed tomography thermometry via material decomposition and machine learning
Thermal ablation procedures, such as high intensity focused ultrasound and radiofrequency ablation, are often used to eliminate tumors by minimally invasively heating a focal region. For this task, real-time 3...
Citation: Visual Computing for Industry, Biomedicine, and Art 2023 6:2 -
An efficient non-iterative smoothed particle hydrodynamics fluid simulation method with variable smoothing length
In classical smoothed particle hydrodynamics (SPH) fluid simulation approaches, the smoothing length of Lagrangian particles is typically constant. One major disadvantage is the lack of adaptiveness, which may...
Citation: Visual Computing for Industry, Biomedicine, and Art 2023 6:1 -
Survey on computational 3D visual optical art design
Visual arts refer to art experienced primarily through vision. 3D visual optical art is one of them. Artists use their rich imagination and experience to combine light and objects to give viewers an unforgetta...
Citation: Visual Computing for Industry, Biomedicine, and Art 2022 5:31 -
Deep learning tomographic reconstruction through hierarchical decomposition of domain transforms
Deep learning (DL) has shown unprecedented performance for many image analysis and image enhancement tasks. Yet, solving large-scale inverse problems like tomographic reconstruction remains challenging for DL....
Citation: Visual Computing for Industry, Biomedicine, and Art 2022 5:30 -
Cardiac CT blooming artifacts: clinical significance, root causes and potential solutions
This review paper aims to summarize cardiac CT blooming artifacts, how they present clinically and what their root causes and potential solutions are. A literature survey was performed covering any publication...
Citation: Visual Computing for Industry, Biomedicine, and Art 2022 5:29 -
Optimization design of two-stage amplification micro-drive system without additional motion based on particle swarm optimization algorithm
With the increasing requirements of precision mechanical systems in electronic packaging, ultra-precision machining, biomedicine and other high-tech fields, it is necessary to study a precision two-stage ampli...
Citation: Visual Computing for Industry, Biomedicine, and Art 2022 5:28 -
Reinforcement learning method for machining deformation control based on meta-invariant feature space
Precise control of machining deformation is crucial for improving the manufacturing quality of structural aerospace components. In the machining process, different batches of blanks have different residual str...
Citation: Visual Computing for Industry, Biomedicine, and Art 2022 5:27 -
Machine learning for enumeration of cell colony forming units
As one of the most widely used assays in biological research, an enumeration of the bacterial cell colonies is an important but time-consuming and labor-intensive process. To speed up the colony counting, a ma...
Citation: Visual Computing for Industry, Biomedicine, and Art 2022 5:26 -
Two fully automated data-driven 3D whole-breast segmentation strategies in MRI for MR-based breast density using image registration and U-Net with a focus on reproducibility
Presence of higher breast density (BD) and persistence over time are risk factors for breast cancer. A quantitatively accurate and highly reproducible BD measure that relies on precise and reproducible whole-b...
Citation: Visual Computing for Industry, Biomedicine, and Art 2022 5:25
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Citation Impact 2023
Journal Impact Factor: 3.2
5-year Journal Impact Factor: 3.8
Source Normalized Impact per Paper (SNIP): 1.126
SCImago Journal Rank (SJR): 0.600Speed 2023
Submission to first editorial decision (median days): 8
Submission to acceptance (median days): 116Usage 2023
Downloads: 294,735
Altmetric mentions: 28 -
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- ISSN: 2524-4442 (electronic)