ACAI

Crowd counting has been a fundamental yet challenging problem in pattern recognition. Most recent deep models for crowd counting rely on Convolutional Neural Networks (CNNs). Although CNN visual features comprise the spatial and channel features, ...

The goal of the open-domain table QA task is to answer a question based on retrieving and extracting information from a large corpus of structured tables. Currently, the accuracy of the most popular framework in open-domain QA: the two-stage retrieval, ...

Task scheduling plays an important role in query execution, which affects the response time and system throughput of queries. Current database systems use simple heuristic algorithms to determine the order of scheduled tasks and executor allocation. ...

Fine-grained visual classification (FGVC) has always been subjecting to large intra-class variances and fine inter-class variances. How to seek discriminative features as many as possible is key factor for FGVC. Traditional FGVC methods tended to adopt ...

During the rapid development of deep learning, the multi-label recognition task has achieved pretty performance. Recently, the emergence of graph convolution network (GCN) has further improved the accuracy of multi-label recognition. However, in the ...

Recent studies have shown that the interaction between protein and ATP is closely related to human diseases, and the ATP-binding sites in protein sequences have become the focus of drug design. In order to improve the prediction accuracy of Protein-ATP ...

In the last decade, several approaches have been proposed for regularizing deeper and wider neural networks (NNs), which is of importance in areas like image classification. It is now common practice to incorporate several regularization approaches in ...

In the past decade, driven by the policy of maximizing the consumption of renewable energy, renewable energy is being integrated into the power grid in the form of centralized power generation or decentralized power generation. The volatility and ...

With the continuous expansion of the scale of wind power, it is necessary to adapt to the change of wind farm output to achieve the consumption of wind power, in order to reduce the total power loss of the entire alternating current (AC) and direct ...

Chronic diseases are the kind of diseases that cause the most severe disease burden in China and have brought significant challenges to the health of our people. With the increase of its global prevalence, it has become a serious global public health ...

Infrared detector is an important device with a wide range of applications. Based on the fault sensitive parameter data of infrared detectors, this paper studies the fault classification and fault prediction model of infrared detectors by using machine ...

In order to improve the hit ratio of lost customers in telecom industry, a combination prediction model of customer churn based on one-dimensional convolutional neural network(1DCNN) and gradient boosting decision tree(GBDT) is proposed. Firstly, ...

Table-to-Text generation is to express the information in the table in words. Considering the simplicity and logic of the statement, the task of logical Table-to-Text generation is derived. Logical Table-to-Text generation is to generate logically ...

In recent years, China's maritime construction has been gradually strengthened, and the security of our territorial waters has become a top priority. In this paper, we propose a self-attentive mechanism-based target detection model for YOLO-v3SAR images,...

An important problem to be solved in reliability simulation of electronic components is to build component-level reliability models based on device-level evaluation results. When the structure or device information and connection composition information ...

Sleep apnea syndrome (SAS) is a common sleep problem, among which obstructive sleep apnea (OSA) is the most common. It is estimated that 936 million adults aged 30-69 years suffer from mild to severe obstructive sleep apnea that can result in poor sleep ...

The nonnegative matrix factorization algorithm is an effective data dimensionality reduction method. The principle is to convert the image into a nonnegative linear combination of low dimensional basis images. Nonnegative matrix factorization can be ...

Rainy image generation aims to transfer images from standard domains such as daytime into rainy domains. Related researches can be divided into unsupervised methods and supervised methods according to use of semantic label constraints. The ...

Physics-informed neural networks (PINNs) have recently been demonstrated to be effective for the numerical solution of differential equations, with the advantage of small real labelled data needed. However, the performance of PINN greatly depends on ...

Data collected from software applications such as issue management systems or version control systems are abstract and require their thorough and comprehensive analysis. Automated issue generation is an understudied area in automated software ...

Detecting scene text has been a challenging task due to the complex geometric layouts of texts. We can broadly classify the state-of-the-art scene text detection methods into two categories. The first category is the top-down methods, which view text ...

This work aims to lip-read Bengali words from talking faces without using audio. Lip reading for English words and sentences is well explored in literature. However, to our knowledge, we are the first to explore this for Bengali words, a language spoken ...

In this paper, a new deep neural network (DNN) ultrasonic beamformer was proposed to suppress off-axis scattering and improve image quality. The simulated channel signals from cysts and single point targets were decomposed by wavelet, and then the ...

Electromagnetic pattern is an image generated from near field electromagnetic field of a device such as microprogrammed control unit (MCU) when it is working. Many Electro-Magnetic Interference (EMI) sources can be located using the electromagnetic ...

Model is required to learn from dynamic data stream under incremental object detection task. However, traditional object detection model fails to deal with this scenario. Fine-tuning on new task suffers from a fast performance decay of early learned ...

Abstract: Marine ship target recognition can effectively identify the categories of sailing ships and realize effective management of ships. It is strategically important for both civil and military domains, but it is highly demanding in terms of ...

The study of algorithms for Automatic Essay Scoring (AES) currently is motivated by textual essay-scoring datasets constructed by anonymous teachers from schools. We propose VisEssay, the first essay-scoring dataset containing handwriting images. ...

BERT-based models have been widely used for document matching, but they generally do not perform well on the matching of long-form documents, as the sequence length limitation could lead to loss of information in the document. Also, the increased noise ...

We propose an acceleration method for relations search over big data scenario. The relations search is in essence an induced subgraph search of graph data model, which is to search all edges with all adjacent vertices falling into a given vertex set. ...

Depth-Image-Based Rendering (DIBR) technology is widely used in 3D video systems to synthesize virtual views. However, the DIBR rendering process tends to introduce local and global distortions, especially local geometric distortion, that will severely ...