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Found 28 papers, 12 papers with code
Edge-Cloud Polarization and Collaboration: A Comprehensive Survey for AI
However, edge computing, especially edge and cloud collaborative computing, are still in its infancy to announce their success due to the resource-constrained IoT scenarios with very limited algorithms deployed.
Speech recognition for air traffic control via feature learning and end-to-end training
In this work, we propose a new automatic speech recognition (ASR) system based on feature learning and an end-to-end training procedure for air traffic control (ATC) systems.
A Comparative Study of Speaker Role Identification in Air Traffic Communication Using Deep Learning Approaches
Most importantly, a multi-modal speaker role identification network (MMSRINet) is designed to achieve the SRI task by considering both the speech and textual modality features.
Nearest Neighborhood-Based Deep Clustering for Source Data-absent Unsupervised Domain Adaptation
To reach this goal, we construct the nearest neighborhood for every target data and take it as the fundamental clustering unit by building our objective on the geometry.
Restoring degraded speech via a modified diffusion model
We replace the mel-spectrum upsampler in DiffWave with a deep CNN upsampler, which is trained to alter the degraded speech mel-spectrum to match that of the original speech.
CloudAAE: Learning 6D Object Pose Regression with On-line Data Synthesis on Point Clouds
In contrast, this domain gap is considerably smaller and easier to fill for depth information.
M6: A Chinese Multimodal Pretrainer
In this work, we construct the largest dataset for multimodal pretraining in Chinese, which consists of over 1. 9TB images and 292GB texts that cover a wide range of domains.
Sparse-Interest Network for Sequential Recommendation
Our sparse-interest module can adaptively infer a sparse set of concepts for each user from the large concept pool and output multiple embeddings accordingly.
Dynamic Memory based Attention Network for Sequential Recommendation
It segments the overall long behavior sequence into a series of sub-sequences, then trains the model and maintains a set of memory blocks to preserve long-term interests of users.
ATCSpeechNet: A multilingual end-to-end speech recognition framework for air traffic control systems
Finally, by integrating the SRL with ASR, an end-to-end multilingual ASR framework is formulated in a supervised manner, which is able to translate the raw wave into text in one model, i. e., wave-to-text.
Q-SR: An Extensible Optimization Framework for Segment Routing
For the offline setting, we develop a fully polynomial time approximation scheme (FPTAS) which can finds a $(1+\omega)$-approximation solution for any specified $\omega>0$ in time that is a polynomial function of the network size.
Networking and Internet Architecture
Cascade Convolutional Neural Network for Image Super-Resolution
With the development of the super-resolution convolutional neural network (SRCNN), deep learning technique has been widely applied in the field of image super-resolution.
Ranked #1 on
Image Super-Resolution
on BSD200 - 2x upscaling
Self-Adapting Recurrent Models for Object Pushing from Learning in Simulation
In this paper, we collect all training data in a physics simulator and build an LSTM-based model to fit the pushing dynamics.
Robotics
Continuous Learning and Inference of Individual Probability of SARS-CoV-2 Infection Based on Interaction Data
This study presents a new approach to determine the likelihood of asymptomatic carriers of the SARS-CoV-2 virus by using interaction-based continuous learning and inference of individual probability (CLIIP) for contagious ranking.
Contrastive Learning for Debiased Candidate Generation in Large-Scale Recommender Systems
Deep candidate generation (DCG) that narrows down the collection of relevant items from billions to hundreds via representation learning has become prevalent in industrial recommender systems.
Controllable Multi-Interest Framework for Recommendation
Recent works usually give an overall embedding from a user's behavior sequence.
A Mobile Robot Hand-Arm Teleoperation System by Vision and IMU
In this paper, we present a multimodal mobile teleoperation system that consists of a novel vision-based hand pose regression network (Transteleop) and an IMU-based arm tracking method.
Robust Robotic Pouring using Audition and Haptics
Both network training results and robot experiments demonstrate that MP-Net is robust against noise and changes to the task and environment.
6D Object Pose Regression via Supervised Learning on Point Clouds
We use depth information represented by point clouds as the input to both deep networks and geometry-based pose refinement and use separate networks for rotation and translation regression.
Dimensional Reweighting Graph Convolution Networks
In this paper, we propose a method named Dimensional reweighting Graph Convolutional Networks (DrGCNs), to tackle the problem of variance between dimensional information in the node representations of GCNs.
Dimensional Reweighting Graph Convolutional Networks
Graph Convolution Networks (GCNs) are becoming more and more popular for learning node representations on graphs.
Representation Learning for Attributed Multiplex Heterogeneous Network
Network embedding (or graph embedding) has been widely used in many real-world applications.
Ranked #1 on
Link Prediction
on Amazon
Making Sense of Audio Vibration for Liquid Height Estimation in Robotic Pouring
PouringNet is trained on our collected real-world pouring dataset with multimodal sensing data, which contains more than 3000 recordings of audio, force feedback, video and trajectory data of the human hand that performs the pouring task.
Robotics Sound Audio and Speech Processing
PointNetGPD: Detecting Grasp Configurations from Point Sets
In this paper, we propose an end-to-end grasp evaluation model to address the challenging problem of localizing robot grasp configurations directly from the point cloud.
Robotics
Vision-based Teleoperation of Shadow Dexterous Hand using End-to-End Deep Neural Network
In this paper, we present TeachNet, a novel neural network architecture for intuitive and markerless vision-based teleoperation of dexterous robotic hands.
Robotics
Occlusion Resistant Object Rotation Regression from Point Cloud Segments
Rotation estimation of known rigid objects is important for robotic applications such as dexterous manipulation.
Texture Object Segmentation Based on Affine Invariant Texture Detection
To solve the issue of segmenting rich texture images, a novel detection methods based on the affine invariable principle is proposed.
Saliency-guided Adaptive Seeding for Supervoxel Segmentation
We propose a new saliency-guided method for generating supervoxels in 3D space.
