Broadband Cross-Slotted Patch Antenna for 5G Millimeter-Wave Applications Based on Characteristic Mode Analysis
This article proposes a wideband differentially-fed dual-polarized magnetoelectric (ME) dipole for millimeter-wave (mm-Wave) applications. Various electric and magnetic characteristic modes of a […]
Importance-Aware Information Bottleneck Learning Paradigm for Lip Reading
Lip reading is the task of decoding text from speakers’ mouth movements. Numerous deep learning-based methods have been proposed to address this […]
The Many Faces of Edge Intelligence
Edge Intelligence (EI) is an emerging computing and communication paradigm that enables Artificial Intelligence (AI) functionality at the network edge. In this […]
OVE6D
This paper proposes a universal framework called OVE6D for model-based 6D object pose estimation from a single depth image and a target […]
AxIoU
Evaluation measures have a crucial impact on the direction of research. Therefore it is of utmost importance to develop appropriate and reliable […]
Optimal Correction Cost for Object Detection Evaluation
Mean Average Precision (mAP) is the primary evaluation measure for object detection. Although object detection has a broad range of applications mAP […]
An Online Framework for Ephemeral Edge Computing in the Internet of Things
In the Internet of Things (IoT) environment, edge computing can be initiated at anytime and anywhere. However, in an IoT environment, edge […]
PhysFormer
Remote photoplethysmography (rPPG), which aims at measuring heart activities and physiological signals from facial video without any contact, has great potential in […]
Decoupling Makes Weakly Supervised Local Feature Better
Weakly supervised learning can help local feature methods to overcome the obstacle of acquiring a large-scale dataset with densely labeled correspondences. However, […]
Learning Optimal K-space Acquisition and Reconstruction using Physics-Informed Neural Networks
The inherent slow imaging speed of Magnetic Resonance Image (MRI) has spurred the development of various acceleration methods typically through heuristically undersampling […]