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Found 19 papers, 6 papers with code
SRLM: Human-in-Loop Interactive Social Robot Navigation with Large Language Model and Deep Reinforcement Learning
An interactive social robotic assistant must provide services in complex and crowded spaces while adapting its behavior based on real-time human language commands or feedback.
AnaMoDiff: 2D Analogical Motion Diffusion via Disentangled Denoising
We present AnaMoDiff, a novel diffusion-based method for 2D motion analogies that is applied to raw, unannotated videos of articulated characters.
Hyperedge Interaction-aware Hypergraph Neural Network
In this paper, we propose HeIHNN, a hyperedge interaction-aware hypergraph neural network, which captures the interactions among hyperedges during the convolution process and introduce a novel mechanism to enhance information flow between hyperedges and nodes.
Mutual Coupling in RIS-Aided Communication: Model Training and Experimental Validation
This paper investigates the mutual coupling in reconfigurable intelligent surface (RIS)-aided communication.
Progressive Neural Compression for Adaptive Image Offloading under Timing Constraints
It is, therefore, important to develop an adaptive approach that maximizes the inference performance of ML applications under timing constraints and the resource constraints of IoT devices.
Unravel Anomalies: An End-to-end Seasonal-Trend Decomposition Approach for Time Series Anomaly Detection
Traditional Time-series Anomaly Detection (TAD) methods often struggle with the composite nature of complex time-series data and a diverse array of anomalies.
Domestic Activities Classification from Audio Recordings Using Multi-scale Dilated Depthwise Separable Convolutional Network
Domestic activities classification (DAC) from audio recordings aims at classifying audio recordings into pre-defined categories of domestic activities, which is an effective way for estimation of daily activities performed in home environment.
A Wideband Reconfigurable Intelligent Surface for 5G Millimeter-Wave Applications
The measurement results demonstrate that the proposed RIS could maintain a 3 dB peak gain variation bandwidth among various array configurations within 22. 5 to 29. 5 GHz (26. 9%) and with a beam scanning capability of 50{\deg}, making this design a good candidate for 5G mm-wave applications.
Active Coarse-to-Fine Segmentation of Moveable Parts from Real Images
We introduce the first active learning (AL) framework for high-accuracy instance segmentation of moveable parts from RGB images of real indoor scenes.
MECPformer: Multi-estimations Complementary Patch with CNN-Transformers for Weakly Supervised Semantic Segmentation
Given a class, the initial seeds generated based on the transformer may invade regions belonging to other classes.
Weakly supervised Semantic Segmentation
Weakly-Supervised Semantic Segmentation
A Via-less Fully Screen-Printed Reconfigurable Intelligent Surface for 5G Millimeter Wave Communication
In this paper, we propose a via-less fully screen-printed reconfigurable intelligent surface which can establish a second line-of-sight communication from 23. 5GHz to 29. 5GHz.
Query6DoF: Learning Sparse Queries as Implicit Shape Prior for Category-Level 6DoF Pose Estimation
Category-level 6DoF object pose estimation intends to estimate the rotation, translation, and size of unseen objects.
Divergence Results and Convergence of a Variance Reduced Version of ADAM
Under a variance reduction assumption, we show that an ADAM-type algorithm converges, which means that it is the variance of gradients that causes the divergence of original ADAM.
Adaptive Edge Offloading for Image Classification Under Rate Limit
Because of limited computing capacity, embedded devices rely on a parsimonious classification model with uneven accuracy.
Better Pseudo-label: Joint Domain-aware Label and Dual-classifier for Semi-supervised Domain Generalization
Also, considering inconsistent goals between generalization and pseudo-labeling: former prevents overfitting on all source domains while latter might overfit the unlabeled source domains for high accuracy, we employ a dual-classifier to independently perform pseudo-labeling and domain generalization in the training process.
Towards Interpretable Attention Networks for Cervical Cancer Analysis
Here, we evaluate various state-of-the-art deep learning models and attention-based frameworks for the classification of images of multiple cervical cells.
SocialGrid: A TCN-enhanced Method for Online Discussion Forecasting
Based on the nature of the grid, we leverage the Temporal Convolution Network to learn the dynamics at the grid level.
Social and Information Networks
Time-constrained Adaptive Influence Maximization
The well-known influence maximization problem aims at maximizing the influence of one information cascade in a social network by selecting appropriate seed users prior to the diffusion process.
Social and Information Networks
