In the research of green vegetation coverage in field remote sensing image segmentation, crop planting area is often obtained by semantic segmentation images taken from high altitude. This method can be used to obtain rate cultivated land a region (such as country), but it does not reflect real situation particular farmland. Therefore, this paper takes low-altitude farmland build dataset. After comparing several mainstream algorithms, new that more suitable for vacancy proposed....

This article employs an artificial neural network technique to approximate the solution for stagnation point flow with velocity and thermal slip effects, as well radiative heat transfer. The PDE governing system is transformed into a set of coupled ordinary differential systems by incorporating similarity variables. shooting method used obtain dataset in Mathematica. To test precision suggested model, operations training, testing, validation are performed, results compared reference dataset....

Rice pests are one of the main factors affecting rice yield. The accurate identification facilitates timely preventive measures to avoid economic losses. Some existing open source datasets related pest mostly include only a small number samples, or suffer from inter-class and intra-class variance data imbalance challenges, which limit application deep learning techniques in field identification. In this paper, based on IP102 dataset, we first reorganized large-scale dataset for by Web...

The occurrence of pests at high frequencies has been identified as a major cause reduced citrus yields, and early detection prevention are great significance to pest control. At present, studies related identification using deep learning suffer from unbalanced sample sizes between data set classes, which may slow convergence network models low accuracy. To address the above problems, this study built dataset including 5182 images in 14 categories. Firstly, we expanded 21,000 by Attentive...

As a core device, electromagnetic clutch is increasingly used in various fields such as automatic control systems. This paper introduces the basic principles, components and key role of mechanical connection disconnection. By analyzing historical development clutch, it points out how technological progress has promoted its application different fields, including industrial automation, automotive braking system special fields. With new materials technologies, faces challenges opportunities....

In recent years, due to its strong nonlinear mapping and research capacities, the convolutional neural network (CNN) has been widely used in field of hyperspectral image (HSI) processing. Recently, pixel pair features (PPFs) spatial PPFs (SPPFs) for HSI classification have served as new tools feature extraction. this paper, on top PPF, improved subtraction (subtraction-PPFs) are applied target detection. Unlike original PPF SPPF, subtraction-PPF considers classes afford CNN, a detection...

Fast, accurate, and non-destructive large-scale detection of sweet cherry ripeness is the key to determining optimal harvesting period accurate grading by ripeness. Due complexity variability orchard environment multi-scale, obscured, even overlapping fruit, there are still problems low accuracy using mainstream algorithm YOLOX in absence a large amount tagging data. In this paper, we proposed an improved target quickly accurately detect categories complex environments. Firstly, took total...

Visible near-infrared spectroscopy (VNIR) is extensively researched for obtaining soil property information due to its rapid, cost-effective, and environmentally friendly advantages. Despite widespread application significant achievements in analysis, current prediction models continue suffer from low accuracy. To address this issue, we propose a convolutional neural network model that can achieve high-precision by creating 2D multi-channel inputs applying multi-scale spatial attention...

Blockchain technology is the underlying of bitcoin.The bitcoin can be used to consume and exchange real currencies, because blockchain provide credit certificate online transaction, all transaction related information encrypted stored in blockchain.So, it safe decentralized, will reduce cost widely used.Another important feature non-modifiable.Since recorded not changeable, this facilitates audit work.Because work designed testify whether transactions matters are truthfully recorded.It...

The accurate segmentation of significant rice diseases and assessment the degree disease damage are keys to their early diagnosis intelligent monitoring core pest control information management. Deep learning applied detection can significantly improve accuracy identification but requires a large number training samples determine optimal parameters model. This study proposed lightweight network based on copy paste semantic for region severity assessment. First, dataset was selected collated...

The accurate identification of crop aphids is an important aspect improving agricultural productivity. Aphids are characterised by small targets and a body colour similar to their surroundings. Even the most advanced detectors can experience problems such as low detection accuracy high number missed detections. In this paper, multi-stream target model proposed for fast in complex backgrounds. First, inspired human visual system, we propose bionic attention (BA) approach. Unlike previous...

Utilizing deep learning for semantic segmentation of cropland from remote sensing imagery has become a crucial technique in land surveys. Cropland illustrates diverse morphologies and degrees fragmentation on the Earth’s surface, underscoring importance accurately perceiving complex boundaries which are effective segmentation. This paper introduces UNet-like boundary-aware compensation model BAFormer. typically exhibit rapid transformations pixel values texture features, often appearing as...

This paper proposes a hyperspectral target detection framework with convolutional neural network (CNN). The number of training samples is first sufficiently enlarged by subtraction method to maximize the advantages multilayer CNN. Next, CNN given function labelling new pixels subtracted between and background classes as 1, within both same different 0. Finally, for each testing pixel, difference central pixel its adjacent input into framework. If belongs target, output score close label....

It is of great significance to realize the low cost and fast statistics wheat ears predict yield. At present, a variety methods have been applied measurement planting density, although these can count wheat, they are expensive difficult be put into actual production. In order further improve accuracy ear identification detection counting under field environment, based on image processing deep learning technology, EfficientDet algorithm proposed detect image. The idea frame out in then...

Frequent pest infestations in rice can substantially decrease yield, severely hindering agricultural production. Computer vision assist farmers timely locating and removing partial or even entire plants infested with pests, achieving control. However, the size population density variance of paddy pests commonly cause interclass intraclass differences datasets, as well an imbalance hard samples. In addition, existing deep learning models struggle to balance compactness high detection...

The difficulties in tea shoot recognition are that the is affected by lighting conditions, it challenging to segment images with similar backgrounds color, and occlusion overlap between leaves.To solve problem of low accuracy dense small object detection shoots, this paper proposes a real-time algorithm based on multimodal optimization. First, RGB, depth, infrared collected form image set, complete labeling performed. Then, YOLOv5 model improved applied tiny detection. Secondly, model,...

Abstract Mixing is not much used in the high-frequency literature so far. However, mixing a common weakly dependent property of continuous and discrete stochastic processes, such as Gaussian, Ornstein–Uhlenberck (OU), Vasicek, CIR, CKLS, logistic diffusion, generalized double-well diffusion processes. So, long-span data typically have weak dependence, using to study them also an alternative approach. In this paper, we give some moment inequalities for with ϕ -mixing, ρ α -mixing. These are...

Abstract It is enormously crucial to bring sustainable development for multinational corporations by incorporating distinct methods productively drive businesses sustainably aligning the corporation's and stakeholders' interests. The study explores connections among corporate social responsibility, ecological manufacturing, green buying intentions of external stakeholders such as consumers drawing on descriptive approach stakeholder theory. First, this examines relationships between...

This investigation's primary objective is to analyze the fluid dynamics and heat transfer enhancement in an irregular enclosure. Several physical phenomena such as Alumina-water nanofluids, magnetic field, non-uniform heating amplitude of are taken into account. A thorough investigation using machine learning algorithms (MLAs) computational (CFD) carried out. Initially, for CFD phase coupled non-linear dimensionless governing equations considered problem solved numerically by adapting a...

Seismic inverse problems aim to infer the properties of subsurface geology, such as elastic and petrophysical properties. Existing seismic inversion methods for joint estimation these are mainly based either on Gassmann theory prestack data processed with stochastic optimisation techniques or Wyllie formula poststack by deterministic techniques. The purpose this study is develop a strategy from equations Given poor-quality data, two regularisation parameters introduced control trade-off...