Camouflaged Object Detection (COD) aims to identify and segment objects that blend into their surroundings. Since the color texture of camouflaged are extremely similar surrounding environment, it is super challenging for vision models precisely detect them. Inspired by research on biology evolution, we introduce depth information as an additional cue help break camouflage, which can provide spatial texture-free separation foreground background. To dig clues in both RGB modalities,...

The EDM process, which was generally accepted as a thermal significantly affected by the characteristic of heat flux plasma. Different type sources have been proposed many researchers to investigate process simulating temperature distribution in electrodes based on thermo physical mod els. However, there exists great difference between different types sources. In this paper, new method investigation plasma proposed. investigated comparing boundary melted material crater obtained...

In the real world, multimodal sentiment analysis (MSA) enables capture and of sentiments by fusing information, thereby enhancing understanding real-world environments. The key challenges lie in handling noise acquired data achieving effective fusion. When processing data, existing methods utilize combination features to mitigate errors word recognition caused performance limitations automatic speech (ASR) models. However, there still remains problem how more efficiently combine different...

Abstract The susceptibility of 316L stainless steel to crevice corrosion was investigated by using immersion test and electrochemical test. Three kinds crevices including 316L‐to‐polytetrafluoroethylene (PTFE) crevice, 316L‐to‐fluoroelastomeric (FKM) 316L‐to‐316L were tested in artificial seawater at 50°C. results indicate that specimen is the most susceptible when it coupled former, while least FKM former. It suggests during submersible solenoid valve design, metal‐to‐metal should be...

Multimodal sentiment analysis models can determine users’ sentiments by utilizing rich information from various sources (e.g., textual, visual, and audio). However, there are two key challenges when deploying the model in real-world environments: (1) limitations of relying on performance automatic speech recognition (ASR) lead to errors recognizing words, which may mislead textual modality, (2) variations density across modalities complicate development a high-quality fusion framework. To...

In the general domain, large multimodal models (LMMs) have achieved significant advancements, yet challenges persist in applying them to specific fields, especially agriculture. As backbone of global economy, agriculture confronts numerous challenges, with pests and diseases being particularly concerning due their complexity, variability, rapid spread, high resistance. This paper specifically addresses these issues. We construct first instruction-following dataset agricultural covering over...

Abstract Acid fracturing is widely used as an effective reconstruction measure in sour gas reservoirs, but sulfur and ferrous sulfide plugging are still problems reservoir secondary damage. In order to simulate damage the presence of ferric ion residual acid, artificial core with supersaturated natural was adopted a sample. A depletion-type experiment carried out observe precipitation core. The results show that color became dark weight increased. Permeability decreased increased time...

Summary Almost half of Western Canada's natural-gas production comes from the Triassic-aged Montney formation, which is rich in condensate. It significant to efficiently develop liquid-rich formation. The objective this study investigate phase behaviors and condensate blockage Further, development potential formation timing gas reinjection were fully discussed. In study, compositional field scale numerical model construct simulate distribution during long-term produced injection periods a...

Summary In seismic data processing, anisotropic parameter modeling plays an important role in the migration imaging results. Traditional methods rely on a large amount of expert knowledge and have poor applicability. this paper, wave field snapshot set is constructed method based BP neural network proposed. First, homogeneous velocity model used to construct through numerical simulation. Then, carry out regression distribution. The experimental results show that has good applicability great...

Summary In seismic data processing, anisotropic parameter modeling plays an important role in the migration imaging results. Traditional methods rely on a large amount of expert knowledge and have poor applicability. this paper, snapshot set wave field is constructed method based residual network proposed. Firstly, homogeneous velocity model used to construct through numerical simulation. Then, deep carry out regression distribution. The experimental results show that error distribution...