In small-footprint end-to-end keyword spotting, it is often expensive and time-consuming to acquire sufficient labels in various speech scenarios. To overcome this problem, transfer learning leverages the rich knowledge of the auxiliary domain to ...

• STSL is proposed for improving the accuracy of CDKWS in various speech scenarios.
• STSL avoids negative transfer by actively selecting source samples for TL.
• STSL aligns TL and active selection to learn a domain-invariant projection ...

The integration of Artificial Intelligence (AI) in the education industry has emerged as a dominant trend, particularly in the field of language education and learning. This study employs advanced visualization tools, such as VOSviewer, to conduct a ...

The quantitative analysis of cells is crucial for clinical diagnosis, and effective analysis requires accurate detection and classification. Using point annotations for weakly supervised learning is a common approach for cell recognition, which ...

This paper proposes a Robust Spatial-Temporal Graph Neural Network (RSTGNN), which overcomes the limitations faced by graph-based models against dynamic graph perturbations using robust spatial-temporal self-attentions to learn dynamic graph ...

Bibliometric mapping is widely used in educational technology research to visualize research field development (e.g. the current status and trend). However, there has been limited research examining the present state, challenges, and potential ...

Time series classification on edge devices has received considerable attention in recent years, and it is often conducted on the assumption that the training and testing data are drawn from the same distribution. However, in practical IoT ...

Sound source localization (SSL) has been widely applied in industrial and civil fields. And with the development of wearable devices and the Internet of Things (IoT), it is attractive to deploy the SSL system onto embedded and portable devices. However, ...

Emerging autonomous vehicles equip multiple high-throughput sensors to enable automatic driving, such as multiline lidars and high-definition cameras. Existing automotive embedded systems usually employ software stacks to receive and preprocess high-...

Federated Learning (FL) is a novel distributed machine learning, which allows thousands of edge devices to train models locally without uploading data to the central server. Since devices in real federated settings are resource-...

Small-footprint keyword spotting has received considerable attention in recent years, which is often conducted on the assumption that the predefined keywords in training and testing data are obtained under the same condition. However, ...

Memristor-based memory computing has attracted much attention recently. By combining the storability and computability of memristor devices together, the memristor-based in-memory computing could break the so-called von Neumann bottleneck. Logic-...

• Global correlation map improves the performance of regression.
• The impacts of the consistency of three cycles differ.
• The smoothness loss relive the irrationality of the aligned results.

Background and objective: Functional gastrointestinal disorders (FGIDs) are reported as worldwide gastrointestinal (GI) diseases. GI motility assessment can assist the diagnosis of patients with intestine motility dysfunction. Wireless capsule ...

Recently, adopting large cache blocks has received widespread attention in server-side storage caching. Besides reducing the management overheads of cache blocks, it can significantly boost the I/O throughput. However, although using large blocks ...

In order to optimize the reactive power characteristics of synchronous condensers and improve the capability of condensers to support the voltage of AC systems, in this paper, the outer loop control of the reactive power of condensers and the outer loop ...

Traditional approaches generally focus on the privacy of user’s identity in a smart IoT environment. Privacy of user’s behavior pattern is an important research issue to address smart technology towards improving user’s life. User’s behavior pattern ...

Neural networks (NN) have gained great success in visual object recognition and natural language processing, but this kind of data-intensive applications requires huge data movements between computing units and memory. Emerging resistive random-access ...

Travel route preferences can strongly interact with the events that happened in networked traveling, and this coevolving phenomena are essential in providing theoretical foundations for travel route recommendation and predicting collective behaviour in ...

Wireless capsule endoscopy (WCE) is a gastrointestinal examination technology, which can help find the polyps in small bowel noninvasively. The computer-aided polyp recognition systems based on deep learning require large amounts of manually annotated ...

As Autonomous Vehicles (AVs) become possible for E-hailing services operate, especially when telecom companies start deploying next-generation wireless networks (known as 5G), many new technologies may be applied in these vehicles. Dynamic-route-switching ...

For user-based collaborative filtering, the similarity methods used to calculate the target user’s neighbors are very important. More similar neighbors lead to better recommendations and more accurate results. There are a lot of similarity ...