CCRIS

At present, the algorithm for virtual liver cutting requires a lot of computation, has poor real-time performance, and is easy to produce degenerated triangle and deformed triangle, and the physical characteristics are lost during the cutting process. ...

Effective suppression of speckle noise in ultrasound images is of great significance for improving image quality and clinical diagnostic analysis. The traditional edge enhancement nonlinear coherent diffusion (EENCD) and multi-scale filtering based on ...

This paper proposes a multi-domain sample classification method based on Baidu API's general object recognition function. we used three datasets in the experiment,including CIFAR-10, CIFAR-100, and Mini-ImageNet. For an unknown sample belonging to these ...

Traffic prediction models play a crucial role in estimating future traffic conditions based on historical data and road network structures. However, these models are vulnerable to adversarial attacks, wherein malicious attackers can manipulate key nodes ...

Federated learning (FL) is an emerging learning paradigm in distributed machine learning (ML) that enables multiple data owners, referred to as clients, to collaboratively train a global model without sharing their local training data. The decentralized ...

To enhance the performance of the Dynamic Window Approach (DWA) algorithm in complex obstacle environments and address its inability to handle negative-weighted edge graphs, this study proposes a path-planning algorithm that combines DWA with informed ...

Cone Beam Computed Tomography (CBCT) has emerged as a valuable imaging technique in dental diagnosis, which enables comprehensive evaluation of dental pathologies, aiding in the diagnosis and treatment planning of complex cases such as impacted teeth, ...

In recent years, additional information in the side of both users and items are more and more common in the natural world. Traditional recommendation methods mainly utilize the the user-item rating information. These information, if properly used, can ...

Joint relational triple extraction is a crucial task in knowledge graph construction. However, most of these methods either perform a large number of redundant predictions on relations, resulting in slower inference speed or ignore the semantic ...

This paper explores the large language models to address the Text-to-SQL task in real-world scenarios in the electricity domain. To tackle the lack of training data and corresponding databases for vertical domain real-world scenarios, the paper devised ...

Encryption not only protects the network security and privacy, but also encrypts attackers’ malicious traffic to evade detection. Thus, how to detect malicious encrypted traffic is critical for network security. From the perspective of privacy, methods ...

Abstract—Aiming at the problem of identifying the characteristics of dust accumulation and shadow of photovoltaic modules, the difference of photovoltaic characteristic curves of dust accumulation and shadow is analyzed in detail, and the time-varying ...

Multi-task imitation learning (MTIL) is an effective approach to training an autonomous agent that is capable of performing multiple tasks using multi-task expert demonstrations. Since different tasks often share similarities, learning them ...

Existing two-stage detectors usually generate oriented proposals based on heuristically defined anchors with different scales, angles, and aspect ratios. This scheme usually suffers from severe memory-consuming and redundant computation. Additionally, ...

To address the problems that the line segments extracted by the existing line segment detectors have local ambiguity and insufficient fitting accuracy, we propose PPL-net, a line segment detector based on the Modified Convolutional Neural Network (CNN) ...

Coronary artery segmentation in digital substraction angiography, as one of the most critical steps in percutaneous coronary intervention (PCI) procedures, has strict accuracy requirements for clinical diagnosis. However, previous studies have seldom ...

Real-time instance segmentation seeks to partition and localize instances with desired efficiency, which has been applied to autonomous driving, robot navigation, and medical image analysis, and so forth. By learning hierarchical features, convolutional ...

Due to the irregularity and disorder of point clouds, point cloud analysis based on deep learning remains a challenging task. Although the previous point cloud analysis networks based on multi-layer perceptions (MLPs) exhibit a simple structure, they ...

In most of the existing mainstream action quality assessment methods, the score regression is performed on a complete action video to obtain the predicted score, which may prevent us from fully exploiting the multi-stage information in action video. In ...

Transformer-like architectures, which are the model of choice in the field of natural language processing, have recently been adapted to computer vision (CV) fields and demonstrated remarkable effectiveness on various CV tasks. However, current ...

A YOLOv7-based multi-scale vehicle detection method for expressways is proposed for the problem of low accuracy of multi-scale vehicle detection due to insufficient extraction and representation of vehicle features in multi-scale vehicle detection in ...

Table-to-text generation is designed to generate descriptive natural language for structured tables that conforms to objective facts and follows the source data. The current challenge in this field is to capture the structural information of the table ...

Starting from the concept, application scenarios and research significance of text filling, this paper divides text filling algorithms into two categories: traditional methods and deep learning, summarizes the development process of text filling ...

Chinese implicit complex sentence relation recognition aims to analyze the semantic logical relationships between two sub-sentences. The main challenge lies in capturing accurate semantic interactions due to the absence of explicit conjunctions. ...

Traditional culture refers to a culture that has evolved from civilization and can reflect the characteristics and spirit of a nation. However, at present, the traditional cultural ontology only focuses on modeling and data organization of a certain ...

The recognition of mixed-bandwidth audio presents a challenge for both academic and industrial fields, with potentially greater implications for the latter. In this paper, we present a unified ASR architecture for mixed-bandwidth audio's recognition, ...

Abstract—The operational efficiency of photovoltaic energy storage charging stations affects their economic benefits and grid-side power quality. To address the problem of non-essential losses due to insufficient consideration of operational efficiency ...

Interactive characteristics exist in multi-DC (multi-infeed-multi-outlet) transmission system at both the sending and the receiving end, coupling effect between transmission lines is further strengthened on the basis of the traditional multi-infeed ...

In this paper, a vector-fitting-based impedance reshaping method for sub-synchronous oscillation suppression in a converter-dominated system is proposed to enhance system damping. In this method, an impedance network model is first established based on ...

With the development of renewable energy technologies and the emergence of distributed power generation devices, traditional centralized power trading markets no longer meet people's transactional needs. Peer-to-peer (P2P) electricity trading within ...