Academic Articles & Research Papers

Frozen Weights as Prior for Parameter-Efficient Fine-Tuning

In the fields of natural language processing and computer vision, the emergence of large pre-trained models has led to the adoption of fine-tuning them for downstream tasks as an important paradigm. However, the full fine-tuning approach of...

A Comprehensive Joint Learning System to Detect Skin Cancer

Skin, the body’s biggest organ and a barrier against heat, light, damage, and infection can be affected by many diseases. However, a correct diagnosis can lead to proper treatment. Skin diseases must be identified early to reduce ski...

Research on Landscape Perception and Visual Attributes Based on Social Media Data—A Case Study on Wuhan University

With the rapid rise of social media, the photo-taking behavior of tourists and their uploaded photos provide a new perspective to explore landscape visual characters. In this study, we provide methodological advancements for assessing lands...

A Video Frame Prediction Method Based on Latent-Space Autoregressive Modeling

Video prediction is a fundamental task in computer vision with broad applications in intelligent robotics, autonomous driving, and related fields. However, existing methods often struggle to simultaneously model long-term temporal dependenc...

Structural characteristics and policy differences of digital health management policies in China: A quantitative analysis based on the PMC index model.

Image fusion method based on simultaneous sparse representation with non‐subsampled contourlet transform

The image fusion method based on sparse representation in the single‐scale image domain has produced better fusion results than the classic methods based on multi‐scale analysis nowadays. However, due to the limited number of dictionary ato...

Remote sensing image road network detection based on channel attention mechanism

Extracting and detecting road network consistency from high-resolution remote sensing images has been a hot and difficult problem in the computer vision. Although it has made significant progress, there is still a phenomenon of high trainin...

Convolutional-de-convolutional neural networks for recognition of surgical workflow

Computer-assisted surgery (CAS) has occupied an important position in modern surgery, further stimulating the progress of methodology and technology. In recent years, a large number of computer vision-based methods have been widely used in ...

Feature Rescaling and Fusion for Tiny Object Detection

Recent years have witnessed rapid developments on computer vision, however, there are still challenges in detecting tiny objects in a large-scale background. The tiny objects knowledge become sparse and weak due to their tiny size, which ma...

A Lightweight Reconstruction Model via a Neural Network for a Video Super-Resolution Model

Super-resolution in image and video processing has been a challenge in computer vision, with its progression creating substantial societal ramifications. More specifically, video super-resolution methodologies aim to restore spatial details...

Enhanced Combined Techniques for Interval-Valued Intuitionistic Fuzzy Multiple-Attribute Group Decision-Making and Applications to Quality Evaluation of Large-Scale Multi-View 3D Reconstruction

With the widespread application of computer vision in many fields, quickly and accurately obtaining the three-dimensional information covered by the target object has become a concern in the field of vision research. Large scale multi view ...

Artificial intelligence literacy and associated factors among gastroenterologists in China: findings from a multicenter survey with nationwide geographic coverage.

Online visual tracking by integrating spatio‐temporal cues

The performance of online visual trackers has improved significantly, but designing an effective appearance‐adaptive model is still a challenging task because of the accumulation of errors during the model updating with newly obtained resul...

A Novel Mixed-Precision Quantization Approach for CNNs

Model size and inference speed have brought about major challenges for the deployment of Convolutional Neural Networks (CNNs) in many applications. An effective approach to address this issue is model quantization, which achieves network co...

DSpix2pix: A New Dual-Style Controlled Reconstruction Network for Remote Sensing Image Super-Resolution

Super-resolution reconstruction is a critical task in remote sensing image classification, and generative adversarial networks (GANs) have emerged as a dominant approach in this field. Traditional generative networks often produce low-quali...

Editorial: Emerging sustainable and green technologies for improving agricultural production

Thangka Mural Line Drawing Based on Cross Dense Residual Architecture and Hard Pixel Balancing

Thangka murals are precious cultural heritage for Tibetan history, literature, and art. Digital line drawing of Thangka murals plays a vital role not only as an abstracted expression of Thangka for art appreciation but also as a fundamental...

Autonomous Nanomedicine: Closing the Biological Validation Gap.

A lightweight fully convolutional neural network for efficient and accurate tunnel crack detection

Introduction: Crack damage is a significant issue in tunnel environments, requiring efficient and reliable detection to ensure structural integrity. Many existing solutions are computationally expensive, making them unsuitable for the tight...

Impact of Water Depth on Subway Emergency Evacuation in Flood Scenarios

[Objective] Evacuation bottlenecks for subway stations in flood scenarios are investigated to enhance subway station personnel evacuation efficiency under water inundation and backflow conditions, and provide insights for developing subway ...