Multi-view stereo based on learning is a critical task in three-dimensional reconstruction, enabling the effective inference of depth maps and the reconstruction of fine-grained scene geometry. However, the results obtained by current popular 3D reconstruction methods are not precise, and achieving high-accuracy scene reconstruction remains challenging due to the pervasive impact of feature extraction and the poor correlation between cost and volume. In addressing these issues, we propose a cascade deep residual inference network to enhance the efficiency and accuracy of multi-view stereo depth estimation.
View Article and Find Full Text PDFAlthough 3D reconstruction has been widely used in many fields as a key component of environment perception, existing technologies still have the potential for further improvement in 3D scene reconstruction. We propose an improved reconstruction algorithm based on the MVSNet network architecture. To glean richer pixel details from images, we suggest deploying a DE module integrated with a residual framework, which supplants the prevailing feature extraction mechanism.
View Article and Find Full Text PDFIntroduction: Moyamoya disease (MMD) is associated with a risk of postoperative cerebral hyperperfusion syndrome (CHS) after revascularization surgery. This study aimed to explore the feasibility of using three-dimensional pulsed arterial spin labeling (3D PASL) and phase contrast (PC) magnetic resonance imaging (MRI) for predicting CHS occurrence in patients with MMD before revascularization surgery.
Methods: Overall, 191 adult patients (207 hemispheres) with MMD who underwent combined revascularization surgery were included in this study.
Sensors (Basel)
September 2023
The pursuit of higher recognition accuracy and speed with smaller model sizes has been a major research topic in the detection of surface defects in steel. In this paper, we propose an improved high-speed and high-precision Efficient Fusion Coordination network (EFC-YOLO) without increasing the model's size. Since modifications to enhance feature extraction in shallow networks tend to affect the speed of model inference, in order to simultaneously ensure the accuracy and speed of detection, we add the improved Fusion-Faster module to the backbone network of YOLOv7.
View Article and Find Full Text PDFWith the popularity of ChatGPT, there has been increasing attention towards dialogue systems. Researchers are dedicated to designing a knowledgeable model that can engage in conversations like humans. Traditional seq2seq dialogue models often suffer from limited performance and the issue of generating safe responses.
View Article and Find Full Text PDFPlant diseases and pests have always been major contributors to losses that occur in agriculture. Currently, the use of deep learning-based convolutional neural network models allows for the accurate identification of different types of plant diseases and pests. To enable more efficient identification of plant diseases and pests, we design a novel network architecture called Dise-Efficient based on the EfficientNetV2 model.
View Article and Find Full Text PDFExtractive document summarization (EDS) is usually seen as a sequence labeling task, which extracts sentences from a document one by one to form a summary. However, extracting sentences separately ignores the relationship between the sentences and documents. One solution is to use sentence position information to enhance sentence representation, but this will cause the sentence-leading bias problem, especially in news datasets.
View Article and Find Full Text PDFSince the emergence of new coronaviruses and their variant virus, a large number of medical resources around the world have been put into treatment. In this case, the purpose of this article is to develop a handback intravenous intelligence injection robot, which reduces the direct contact between medical staff and patients and reduces the risk of infection. The core technology of hand back intravenous intelligent robot is a handlet venous vessel detection and segmentation and the position of the needle point position decision.
View Article and Find Full Text PDFAspect-level sentiment classification has been widely used by researchers as a fine-grained sentiment classification task to predict the sentiment polarity of specific aspect words in a given sentence. Previous studies have shown relatively good experimental results using graph convolutional networks, so more and more approaches are beginning to exploit sentence structure information for this task. However, these methods do not link aspect word and context well.
View Article and Find Full Text PDFObjective: To explore the feasibility of 2D phase-contrast MRI (PC-MRI) and intravoxel incoherent motion (IVIM) MRI to assess cerebrovascular hemodynamic changes after surgery in adult patients with moyamoya disease (MMD).
Methods: In total, 33 patients with MMD who underwent 2D PC-MRI and IVIM examinations before and after surgery were enrolled. Postsurgical changes in peak and average velocities, average flow, forward volume, and the area of superficial temporal (STA), internal carotid (ICA), external carotid (ECA), and vertebral (VA) arteries were evaluated.
Objective: This study aimed to investigate the feasibility of preoperative intravoxel incoherent motion (IVIM) MRI for the screening of high-risk patients with moyamoya disease (MMD) who may develop postoperative cerebral hyperperfusion syndrome (CHS).
Methods: This study composed of two parts. In the first part 24 MMD patients and 24 control volunteers were enrolled.
Background: To determine the prostate cancer biochemical recurrence-related fusion biopsy characteristics before radical surgery and to establish the risk prediction model of biochemical recurrence of prostate cancer.
Methods: Three hundred and four patients undergoing radical surgery for prostate cancer at Huadong Hospital affiliated to Fudan University between 2009 and 2020 for preoperative magnetic resonance imaging (MRI) before biopsy with suspicious prostate cancer lesions. Each case was followed by a 10 + x needle combination of targeted biopsy (intentional or robotic fusion) with systematic biopsy.