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Found 15 papers, 3 papers with code
S³Net: Semantic-Aware Self-supervised Depth Estimation with Monocular Videos and Synthetic Data
In order to learn such a scalable depth estimation model, we require a ton of data and labels which are targeted towards specific use-cases.
mmFlexible: Flexible Directional Frequency Multiplexing for Multi-user mmWave Networks
Modern mmWave systems have limited scalability due to inflexibility in performing frequency multiplexing.
GreenMO: Virtualized User-proportionate MIMO
The reason is that traditionally MIMO requires a separate RF chain per antenna, so the power consumption scales with number of antennas, instead of number of users, hence becomes energy inefficient.
Spoofing Attack Detection in the Physical Layer with Commutative Neural Networks
In a spoofing attack, an attacker impersonates a legitimate user to access or tamper with data intended for or produced by the legitimate user.
Deep Learning Object Detection Approaches to Signal Identification
Traditionally source identification is solved using threshold based energy detection algorithms.
R-fiducial: Reliable and Scalable Radar Fiducials for Smart mmwave Sensing
Millimeter wave sensing has recently attracted a lot of attention given its environmental robust nature.
RadSegNet: A Reliable Approach to Radar Camera Fusion
Contrary to these approaches, we propose a new method, RadSegNet, that uses a new design philosophy of independent information extraction and truly achieves reliability in all conditions, including occlusions and adverse weather.
Pointillism: Accurate 3D bounding box estimation with multi-radars
We introduce a novel concept of Cross Potential Point Clouds, which uses the spatial diversity induced by multiple radars and solves the problem of noise and sparsity in radar point clouds.
BeamScatter: Scalable, Deployable Long-Range backscatter communication with Beam-Steering
WiFi backscatter tags can enable direct connectivity of IoT devices with commodity WiFi hardware at low power.
Two beams are better than one: Enabling reliable and high throughput mmWave links
Multi-beam links are reliable since they are resilient to occasional blockages of few constituent beams compared to a single-beam system.
WiForce: Wireless Sensing and Localization of Contact Forces on a Space Continuum
Contact force is a natural way for humans to interact with the physical world around us.
Sampling Training Data for Continual Learning Between Robots and the Cloud
Today's robotic fleets are increasingly measuring high-volume video and LIDAR sensory streams, which can be mined for valuable training data, such as rare scenes of road construction sites, to steadily improve robotic perception models.
SSLIDE: Sound Source Localization for Indoors based on Deep Learning
This paper presents SSLIDE, Sound Source Localization for Indoors using DEep learning, which applies deep neural networks (DNNs) with encoder-decoder structure to localize sound sources with random positions in a continuous space.
$S^3$Net: Semantic-Aware Self-supervised Depth Estimation with Monocular Videos and Synthetic Data
We present $S^3$Net, a self-supervised framework which combines these complementary features: we use synthetic and real-world images for training while exploiting geometric, temporal, as well as semantic constraints.
SIGNet: Semantic Instance Aided Unsupervised 3D Geometry Perception
SIGNet is shown to improve upon the state-of-the-art unsupervised learning for depth prediction by 30% (in squared relative error).
Ranked #62 on
Monocular Depth Estimation
on KITTI Eigen split
