As the behavior analysis of human body is more and used in fields intelligent monitoring motion analysis, it great significance to conduct research.The current two-dimensional regression network algorithm models recognition estimation do not consider interrelationships between joint points, resulting missing connections points low accuracy feature maps. Therefore, this study proposes an improved model based on local constraints relational networks, verifies its effectiveness. The...

Illegal construction should be detected as early possible it can damage the environment and economy. However, existing methods for detecting illegal improved in terms of their detection cycles, accuracy, speed. Moreover, there are relatively few valuable real-world image datasets construction. To address these issues, a high-precision real-time model named YEMNet new large-scale dataset objects (ICOS) proposed herein. Our is based on You Only Look Once v3 object model; this adopts...

Obstructive Sleep Apnea Hypopnea Syndrome (OSAHS) is a sleep-related respiratory disease, and sleep snoring its most common direct feature. However, the current detection methods require lot of medical manpower equipment resources, resulting in many OSAHS patients cannot be treated time. Therefore, this paper proposes snore method based on deep learning dataset. The first calculates time-domain waveform, spectrogram, Mel-spectrogram for each audio segment Then, recognized by convolution...

Effective vehicle detection plays a crucial role in various applications cities, including traffic management, urban planning, transport, and surveillance systems. However, existing methods suffer from low recognition accuracy, high computational costs, excessive parameters. To address these challenges, this paper proposed high-precision lightweight detector along with new dataset for construction-related vehicles. The comprises 8425 images across 13 different categories of was based on...

In recent years, the use of vision robots in industrial fields has increased, these are used to capture images workpieces. However, presence light, vibration, and other interferences can cause captured be blurry difficult identify, it have a negative impact on subsequent operations robots. Partial differential equation image denoising emerged as popular research area due its capability eliminating noise retaining edge details. The partial for is high-order, high dimensional, nonlinear,...

<title>Abstract</title> Erasure-coded systems require simultaneous updating of data chunks and parity chunks, thereby leading to high input/output (I/O) overhead. Following these updates, the most recent deltas are dispersed randomly in log, which results prolonged recovery time. This study introduces a novel approach named MPLR, is specifically designed expedite erasure-coded recovery. MPLR uses machine learning categorize files into non-read-only read-only classes, then performs updates...

Abstract Metadata prefetching and data placement are essential to improve access performance for wide-area network file systems. Constructing efficient approaches has been a challenge metadata in concurrent workload scenarios network. This paper proposes placement, wherein fine-grained control of policies variable-size fragment writing utilized maximize the I/O bandwidth distributed files. The proposed approach dynamically detects dominant adaptively adjusts policy scenarios. places written...

The reconstruction of high quality images from a limited number radio-frequency (RF) measurements is crucial for ultrafast plane wave ultrasound (PWUS) imaging system. sparse and low rank model can efficiently exploit the correlation between different channels. However, strategies derived models use convex relaxations matrix <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$l_{1}$</tex> norm to induce sparsity, approximations are widely known...

Magnetic resonance imaging (MRI) reconstruction model based on total variation (TV) regularization can solve some problems, e.g., incomplete reconstruction, blurred imaging, and denoising. However, it has problems such as sensitivity to outliers, poor ability induce the sparsity of gradient domain MR image. In this paper, minimax-concave $L_{p}-$norm (MCTV-L <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</inf> ) is proposed overcome these...