ICCVIT

Two-dimensional human pose estimation is the basis of human behavior understanding, but predicting a reasonable three-dimensional human pose sequence is still a challenging problem. To solve this problem, a pose estimation model named DEFormer based on ...

A new binocular stereo matching algorithm is proposed to solve the problem that the existing stereo matching algorithm is susceptible to noise and pixel mismatch and wrong matching in weak texture areas. First, set the search window and the neighborhood ...

Optimizing the selection of features and channels with satisfactory emotion classification accuracy is important for electroencephalograph (EEG)-based emotion recognition. Here, we propose a novel case-based channel selection method based on ...

In maritime transportation, accurate prediction of AIS-based vessel trajectory has a significant impact on collision-free vessel trajectory prediction. Due to the dense and highly dynamic marine navigation traffic, it is a great challenge to predict the ...

Hyperspectral image(HSI) classification is a crucial topic within remote sensing. Recently, deep self-supervised learning methods have gained widespread use in HSI classification, effectively addressing the scarcity of labeled samples issue. In ...

Smart grid is a new generation of energy infrastructure. Data aggregation is a common method for assessing and protecting electricity consumption in smart grids. Since the existing data aggregation scheme focuses on centralization, it is easy to lead to ...

Information security stemming from Generative Adversarial Network (GAN) variants has garnered significant attention. However, a complete reference model targeting this security problem has yet to be established. This paper selects several GAN variants as ...

Line segment detection is an important part of image feature engineering, with the local-based line segment detection algorithms being the most widely used. Despite the availability of several line segment detection algorithms, their performance ...

Structured light 3D imaging based on Gray code requires accurate pixel light and dark judgment for high-quality reconstruction. This paper proposes a pixel point classification method for fringe images based on the U-Net network to achieve robust and ...

With the increasing popularity of 5G, 5G base stations are facing an increasing number of security threats, and their security status characterization has become a current research hotspot. This paper studies the security feature extraction for RF ...

Accelerating the integrated development of mechanization, informatization and intelligence in weapons and equipment is the only way for the armed forces to realize the modernization of weapons and equipment. However, due to reasons such as network ...

Unmanned aerial vehicle (UAV), with high efficiency, low manpower costs, and flexible convenience, has attracted widespread attention in logistics. UAV trajectory planning is an essential component in this context. Genetic algorithm(GA) is an effective ...

This paper proposes an environment perception algorithm based on the principle of vanishing point in perspective projection and a cascaded multi-variable RBF neural network PID adaptive control method to address the drawbacks of the existing indoor ...

In the field of autonomous driving, a novel approach is proposed for detecting and recognizing surrounding vehicles targets. The proposed method combines multiple attention mechanisms within a 3D object detection algorithm, drawing inspiration from the ...

As the main expression medium of emotion, facial expression is used to explore personal emotion through facial expression recognition. The convolutional neural network architecture in deep learning can combine the emotion feature extraction and ...

Objective: To evaluate the performance of an artificial intelligence (AI)-based medical analysis tool called uAI-HematomaCare in automatically detecting, classifying, and measuring the volume of acute spontaneous intracranial hemorrhage (ICH) on non-...

This paper presents the Macro Bi-level Optimal Transport model (MBOT model) based on optimal transport theory applied to large aggregated places for crowd evacuation. Optimal transport theory bridges geometry and probability, providing a new way to model ...

Abstract: Cell nucleus segmentation plays a significant role in Computer-Aided systems for cancer diagnosis. However, complex visual features, such as blurring and irregular shapes, increase the difficulty of segmentation. This paper proposes a ...

The current motion decision of autonomous robots is characterised by rigid motion commands, which leads to unsatisfactory motion decision results. To this end, an autonomous robot motion decision algorithm based on decision tree algorithm and deep ...

Fatigue driving can easily lead to traffic accidents. Therefore, fatigue driving behavior needs to be analyzed. Compared to normal driving, human facial expressions in a state of fatigue can be changed. We integrate facial expression recognition ...

Safety has always been one of the most concerned issues in the Architecture Engineering and Construction (AEC) industry, On-Site Construction Safety Management (OCSM)is adopted to ensure the safety of personnel and property during the construction ...

Abstract Artificial intelligence techniques such as machine learning and deep learning are prevalent in the field of medical imaging, especially image segmentation. In the field of medicine, image segmentation helps to diagnose diseases accurately and ...

Canonical correlation analysis (CCA), a method for assessing inter-signal correlation that is widely used to enhance the performance of brain-computer interfaces (BCIs), can play an effective role in detecting steady-state visual evoked potentials (...

The problem of facial expression recognition based on VGG-face transfer learning is studied. In order to solve the problem of incomplete extraction of subtle features in the current facial expression recognition model, a transfer learning facial ...

Estimating transformation parameters between 3D point sets is crucial for various motion-based 3D vision tasks, such as point cloud registration, pose estimation, 3D object recognition, and tracking. Traditional methods rely on optimizing parameters ...

Lung nodules are an early manifestation of lung cancer, and their diagnostic process is of great importance. To address the problems of missed detection, over-segmentation and unclear boundary segmentation in the segmentation process of lung nodules, we ...

This paper introduces a binary classification network that utilizes the Informer Encoder to classify ping pong actions as either correct or incorrect. The dataset used in this study comprises 949 action videos capturing two fundamental ping pong stroke ...

In this paper, a point cloud instance segmentation method is proposed to achieve infrared moving small multi-targets trajectory detection. Different from previous trajectory detection methods that used manually designed features to achieve frame-by-frame ...

Recent advances in artificial intelligence architectures have provided templates for automated composition in music generation. However, these automated composition techniques often suffer from a lack of emotional expression and structural coherence. ...

The current intelligent decision-making algorithms are not comprehensive enough in data search, resulting in poor quality decision results. For this reason intelligent decision algorithms based on hybrid cuckoo algorithms and deep learning are proposed. ...