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The Blockchain 2.0 era integrated with smart contract along with its platforms and applications have experienced explosive growth in recent years. However, many smart contracts deployed in practice are prone to errors and cannot be modified due to the ...

Sentiment analysis is an important natural language processing task that seeks to extract contextual subjective information and perform classification. CNN and Bi-LSTM are two of the most popular models in text-based sentiment analysis. However, with ...

Point-of-Interest (POI) recommendation recommends different personalized services to interested users, which are widely used in people's daily life. However, with the massive increase in users and POIs, the POI recommendation system faces the following ...

According to the "national surface water monitoring and evaluation scheme for the 14th Five-Year plan" issued by the Ministry of ecological environment of the people's Republic of China, this study constructs a back propagation (BP) neural network model ...

This study presented the development of a web-based system that visualizes real-time traffic by deploying lightweight and mobile monitoring devices at roadside intersections in the vicinity of Butuan City to assist commuters and drivers in making ...

Abstract: Fruit counting is an integral part of achieving precision orchard management. Accurate counting of the number of fruits on a tree can provide critical information for yield estimation, thus promoting precision agriculture. However, today fruit ...

Abstract: Haze rendering aims to generate realistic nighttime haze images from clear images. The results can be applied to various practical applications, such as nighttime image dehazing algorithms, game scene rendering, shooting filters, etc. We ...

Abstract: Most low-light enhancement methods based on curve estimation do not have the ability of multi-illumination processing. They cannot use one model to process images with different exposure levels. This paper proposes to process multi-...

Due to the complexity of taking photos on foggy days, images captured in the real world are prone to problems of detail loss, color dimness, and low saturation. Considering image dehazing as a problem of detail recovery and color enhancement, a two-...

The training of fully supervised semantic segmentation (FSSS) networks relies on a large amount of data with pixel-level class labels, which limits semantic segmentation's application in practical scenarios. Weakly supervised semantic segmentation (WSSS)...

Aiming at the problems of unclear boundaries and low segmentation accuracy in general real-time semantic segmentation networks, a real-time semantic segmentation network based on improved BiSeNet V1 was proposed. Based on the BiSeNetV1 network, a ...

Brain tumor is one of the common diseases of the central nervous system, and the incidence and death of brain tumors are among the highest in the world. Although the incidence of brain tumors is lower than that of other systemic tumors, due to the wide ...

With the advent of the era of big data, although the relationship between samples can be found from individual clustering of each view, data in the real world generally has multiple representations, and different data representations can complement each ...

Aiming at the limitations of the prior art in the sorting of frequency hopping signals under the condition of low signal-to-noise ratio, this paper proposes a method to reduce the noise of the image through image preprocessing, and then improve ...

Existing video summarization methods are classified into either shot-level or frame-level methods, which are individually used in a general way. This paper investigates the underlying complementarity between the frame-level and shot-level methods, and a ...

Prior self-supervised video object segmentation models directly find pixel correspondences between pairs of frames. Instead, we propose a novel approach of employing superpixel features for learning visual correspondences between frames of a video ...

Keypoint feature extraction algorithms based on manual feature rely on the professional domain knowledge of the designer, and usually perform well in depicting the detail of an image. However, these manual feature-based feature extraction algorithms ...

Few studies present how to implement super resolution (SR) on abdominal Computed Tomography (CT) images. However, in the field of medical imaging, the development of an advanced SR system will potentially improve the clinical diagnosis and prognosis of ...

Ship detection in complex weathers is an important application of object detection approaches in real life. In recent years, ship detection approaches for single weather have gradually matured. However, there are few ship detection approaches for ...

Change detection is a challenging problem in remote sensing applications. In recent years, many Convolutional Neural Network (CNN)-based change detection methods have been proposed due to the rapid development of deep learning techniques. First, the ...