217 Result(s)
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Article
Multi-granularity hypergraph-guided transformer learning framework for visual classification
Fine-grained single-label classification tasks aim to distinguish highly similar categories but often overlook inter-category relationships. Hierarchical multi-granularity visual classification strives to cate...
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Article
OV-DAR: Open-Vocabulary Object Detection and Attributes Recognition
In this paper, we endeavor to localize all potential objects in an image and infer their visual categories, attributes, and shapes, even in instances where certain objects have not been encompassed in the mode...
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Article
OV-VIS: Open-Vocabulary Video Instance Segmentation
Conventionally, the goal of Video Instance Segmentation (VIS) is to segment and categorize objects in videos from a closed set of training categories, lacking the generalization ability to handle novel categor...
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Article
A novel automated framework for fine-grained sentiment analysis of application reviews using deep neural networks
The substantial volume of user feedback contained in application reviews significantly contributes to the development of human-centred software requirement engineering. The abundance of unstructured text data ...
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Article
SCDet: decoupling discriminative representation for dark object detection via supervised contrastive learning
Despite the significant progress made in object detection algorithms, their potential to operate effectively under the low-light environment remains to be fully explored. Recent methods realize dark object det...
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Article
Dynamic datasets and market environments for financial reinforcement learning
The financial market is a particularly challenging playground for deep reinforcement learning due to its unique feature of dynamic datasets. Building high-quality market environments for training financial rei...
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Article
RSGNN: residual structure graph neural network
Compared to conventional artificial neural networks, Graph Neural Networks (GNNs) better handle graph-structured data. Graph topology plays an important role in learning graph representations and impacts the p...
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Article
Multitask learning for image translation and salient object detection from multimodal remote sensing images
This paper presents a novel and efficient multitask learning framework for image translation and saliency detection from remote sensing images, which mainly contains the image translation network-weight sharin...
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Article
A hybrid style transfer with whale optimization algorithm model for textual adversarial attack
Deep learning has been widely used in various research fields. However, researchers have discovered that deep learning models are vulnerable to adversarial attacks. Existing word-level attacks can be seen as a...
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Article
Reinforcement learning from constraints and focal entity shifting in conversational KGQA
The actual needs of users for information are often hidden in multiple question answering (QA) on the same topic. In order to generate answers to users’ current questions, a conversational QA system relies on ...
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Chapter and Conference Paper
3D Human Target Tracking and Localization Based on Millimeter Wave Radar and Visual Fusion
In recent years, 3D object detection has become an important component in the fields of autonomous driving and mobile robots. Current vision-based methods may fail to achieving reliable positioning of a 3D obj...
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Chapter and Conference Paper
Path-Oriented Green Wave Speed Control Model Towards Autonomous Vehicle
The stop-and-start at intersections has become a prominent issue, not only damaging transportation operational efficiency but also leading to energy consumption and pollution
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Chapter and Conference Paper
Design and Development of Digital Circuit Simulation Software Based on Virtual Reality Technology
In order to improve teachers’ teaching efficiency, stimulate students’ interest in learning, increase students’ initiative and consciousness of learning, break through the limitation of physical environment co...
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Chapter and Conference Paper
DFaP: Data Filtering and Purification Against Backdoor Attacks
The rapid development of deep learning has led to a dramatic increase in user demand for training data. As a result, users are often compelled to acquire data from unsecured external sources through automated ...
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Chapter and Conference Paper
Spatial Feature Regularization and Label Decoupling Based Cross-Subject Motor Imagery EEG Decoding
Motor imagery (MI) serves as a vital approach to constructing brain-computer interfaces (BCIs) based on electroencephalogram (EEG) signals. However, the time-variant and label-coupling characteristics of EEG s...
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Chapter and Conference Paper
An Erase Code Based Collaborative Storage Method in RFID Systems
Ensuring the safe and reliable storage of important data under limited storage resources is an important challenge faced by RFID systems. Cooperative storage technology based on network coding can divide the t...
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Chapter and Conference Paper
End-to-End Streaming Customizable Keyword Spotting Based on Text-Adaptive Neural Search
Streaming keyword spotting (KWS) is an important technique for voice assistant wake-up. While KWS with a preset fixed keyword has been well studied, test-time customizable keyword spotting in streaming mode re...
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Chapter and Conference Paper
Efficient Point-Based Single Scale 3D Object Detection from Traffic Scenes
In the field of 3D object detection, the point-based method faces significant limitations due to the need to process large-scale collections of irregular point clouds, resulting in reduced inference speed. To ...
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Chapter and Conference Paper
3RE-Net: Joint Loss-REcovery and Super-REsolution Neural Network for REal-Time Video
Real-time video over the Internet suffers from packet loss and low network bandwidth. The receiving side may receive down-sampled video with damaged frames. In this work, we are motivated to enhance the qualit...
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Article
Multi-speaker DoA Estimation Using Audio and Visual Modality
Traditionally, direction of arrival (DoA) approaches only use a single audio modality. However, humans naturally locate sound sources through auditory and visual clues. Inspired by this motivation, we adopt au...