Artificial Intelligence and Terrestrial Point Clouds for Forest Monitoring

Engineering, Environmental Engineering, Information Science, Computer Science, Artificial Intelligence, Life Sciences, Botany,
deep learning   machine learning   forest inventory   tree characteristics   open data   precision forestry   lidar  

Artificial Intelligence and Terrestrial LiDAR Point Clouds in Forest Monitoring: Academic Report Academic Background With the increasing importance of global climate change and forest resource management, precision forestry has become a key direction in modern forest management. Precision forestry relies on high-precision forest data collection and...

Multimodal Deep Learning Improves Recurrence Risk Prediction in Pediatric Low-Grade Gliomas

Information Science, Artificial Intelligence, Medicine, Neurology, Medical Imaging, Oncology,
pediatric low-grade gliomas   deep learning   postoperative recurrence prediction   multimodal model   magnetic resonance imaging   risk stratification   survival analysis  

Application of Deep Learning in Postoperative Recurrence Prediction for Pediatric Low-Grade Gliomas Background Pediatric Low-Grade Gliomas (PLGGs) are one of the most common types of brain tumors in children, accounting for 30%-50% of all central nervous system tumors in children. Although the prognosis of PLGGs is relatively favorable, the risk of...

Delving Deep into Simplicity Bias for Long-Tailed Image Recognition

Information Science, Computer Science, Artificial Intelligence,
long-tailed image recognition   simplicity bias   deep learning   self-supervised learning   data imbalance  

Academic Background and Problem Statement In recent years, deep neural networks have made significant progress in the field of computer vision, particularly in tasks such as image recognition, object detection, and semantic segmentation. However, even the most advanced deep models struggle when faced with long-tailed distribution data, where the nu...

PICK: Predict and Mask for Semi-Supervised Medical Image Segmentation

Information Science, Computer Science, Artificial Intelligence, Medicine, Medical Imaging,
semi-supervised learning   medical image segmentation   attentive region masking   reconstruction task   deep learning  

Report on the Paper “PICK: Predict and Mask for Semi-Supervised Medical Image Segmentation” Academic Background Accurate segmentation of medical images is crucial in clinical practice, as it provides vital insights into organ/tumor characteristics such as volume, location, and shape. Recent studies have highlighted the significant potential of data...

Heuristic Underwater Perceptual Enhancement with Semantic Collaborative Learning

Engineering, Ocean Engineering, Information Science, Computer Science, Artificial Intelligence,
underwater image enhancement   deep learning   color correlation   object detection   semantic collaborative learning   invertible network   heuristic prior  

Academic Background and Problem Statement Underwater images have significant application value in fields such as marine exploration, underwater robotics, and marine life identification. However, due to the refraction and absorption of light by water, underwater images often suffer from low contrast and color distortion, which severely impacts the a...

Blind Image Quality Assessment: Exploring Content Fidelity Perceptibility via Quality Adversarial Learning

Information Science, Computer Science, Artificial Intelligence,
image quality assessment   no reference   quality adversarial learning   content fidelity   deep learning   image restoration   visual perception  

Exploring Content Fidelity Perceptibility via Quality Adversarial Learning Academic Background Image Quality Assessment (IQA) is a fundamental problem in the field of computer vision, aiming to evaluate the fidelity of visual content in images. IQA has significant applications in areas such as image compression and restoration. Traditional IQA meth...

CSFRNet: Integrating Clothing Status Awareness for Long-Term Person Re-Identification

Information Science, Computer Science, Artificial Intelligence,
long-term person re-identification   clothing status awareness   feature regularization   deep learning   visual surveillance  

Report on the Paper “CSFRNet: Integrating Clothing Status Awareness for Long-Term Person Re-Identification” Introduction Person Re-Identification (Re-ID) is a critical task in visual surveillance, aiming to match individuals across non-overlapping cameras captured at different times and locations. The challenge becomes more complex in Long-Term Per...

Combating Label Noise with a General Surrogate Model for Sample Selection

Information Science, Computer Science, Artificial Intelligence,
label noise   sample selection   deep learning   vision-language model   CLIP model   noise-aware loss   robust training  

Academic Background and Problem Statement With the rapid development of Deep Neural Networks (DNNs), visual intelligence systems have made significant progress in tasks such as image classification, object detection, and video understanding. However, these breakthroughs rely heavily on the collection of high-quality annotated data, which is often t...

From Behavior to Natural Language: Generative Approach for UAV Intent Recognition

Engineering, Aerospace Engineering, Information Science, Computer Science, Artificial Intelligence,
UAV   intent recognition   generative model   cross-modal   time series   deep learning   confrontation environment  

UAV Behavior Intent Recognition Based on Generative Models: A Cross-Modal Study From Behavior to Natural Language Background and Research Objectives In recent years, Unmanned Aerial Vehicle (UAV) technology has advanced rapidly and has found widespread applications in civilian and military domains, including search and rescue, precision agriculture...

Enhancing Aerial Object Detection with Selective Frequency Interaction Network

Engineering, Aerospace Engineering, Information Science, Computer Science, Artificial Intelligence,
aerial object detection   frequency-domain features   selective frequency interaction   convolutional neural networks   feature extraction   deep learning   computer vision  

Selective Frequency Interaction Network for Improved Aerial Object Detection Background and Problem Statement With the advancements in computer vision, aerial object detection has become a critical research focus in remote sensing. This task aims to identify targets such as vehicles or buildings from aerial images captured at varying angles and alt...