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Found 20 papers, 4 papers with code
Accurate Nuclear Segmentation with Center Vector Encoding
Nuclear segmentation is important and frequently demanded for pathology image analysis, yet is also challenging due to nuclear crowdedness and possible occlusion.
Signet Ring Cell Detection With a Semi-supervised Learning Framework
Our framework achieves accurate signet ring cell detection and can be readily applied in the clinical trails.
Attention-Aware Age-Agnostic Visual Place Recognition
Different from conventional VPR settings where the query images and gallery images come from the same domain, we propose a more common but challenging setup where the query images are collected under a new unseen condition.
Large-scale Gastric Cancer Screening and Localization Using Multi-task Deep Neural Network
Gastric cancer is one of the most common cancers, which ranks third among the leading causes of cancer death.
SNR-adaptive deep joint source-channel coding for wireless image transmission
Considering the problem of joint source-channel coding (JSCC) for multi-user transmission of images over noisy channels, an autoencoder-based novel deep joint source-channel coding scheme is proposed in this paper.
Shapley Counterfactual Credits for Multi-Agent Reinforcement Learning
Specifically, Shapley Value and its desired properties are leveraged in deep MARL to credit any combinations of agents, which grants us the capability to estimate the individual credit for each agent.
Hybrid Supervision Learning for Pathology Whole Slide Image Classification
To handle this problem, we propose a hybrid supervision learning framework for this kind of high resolution images with sufficient image-level coarse annotations and a few pixel-level fine labels.
Instance-wise or Class-wise? A Tale of Neighbor Shapley for Concept-based Explanation
Deep neural networks have demonstrated remarkable performance in many data-driven and prediction-oriented applications, and sometimes even perform better than humans.
Deep Joint Source-Channel Coding for Multi-Task Network
The feature generated by the mobile device is transmitted through the wireless channel to the edge server.
S2RL: Do We Really Need to Perceive All States in Deep Multi-Agent Reinforcement Learning?
To this end, we propose a sparse state based MARL (S2RL) framework, which utilizes a sparse attention mechanism to discard irrelevant information in local observations.
Multi-agent Reinforcement Learning
Reinforcement Learning (RL)
+2
SNN-SC: A Spiking Semantic Communication Framework for Feature Transmission
However, most of the existing SC works only transmit analog information on the AWGN channel and cannot be directly used for digital channels.
Window Normalization: Enhancing Point Cloud Understanding by Unifying Inconsistent Point Densities
Existing methods are limited by the inconsistent point densities of different parts in the point cloud.
Ranked #6 on
Semantic Segmentation
on S3DIS
OSP: Boosting Distributed Model Training with 2-stage Synchronization
However, these two types of methods can result in accuracy loss due to discarded gradients and have limited enhancement on the throughput of model synchronization, respectively.
Multi-Objective Optimization for UAV Swarm-Assisted IoT with Virtual Antenna Arrays
The existing UAV-assisted data harvesting and dissemination schemes largely require UAVs to frequently fly between the IoTs and access points, resulting in extra energy and time costs.
Joint Task Offloading and Resource Allocation in Aerial-Terrestrial UAV Networks with Edge and Fog Computing for Post-Disaster Rescue
Unmanned aerial vehicles (UAVs) play an increasingly important role in assisting fast-response post-disaster rescue due to their fast deployment, flexible mobility, and low cost.
Joint Scheduling and Trajectory Optimization of Charging UAV in Wireless Rechargeable Sensor Networks
Wireless rechargeable sensor networks with a charging unmanned aerial vehicle (CUAV) have the broad application prospects in the power supply of the rechargeable sensor nodes (SNs).
UAV Swarm-enabled Collaborative Secure Relay Communications with Time-domain Colluding Eavesdropper
Unmanned aerial vehicles (UAVs) as aerial relays are practically appealing for assisting Internet of Things (IoT) network.
Spiking Semantic Communication for Feature Transmission with HARQ
In Collaborative Intelligence (CI), the Artificial Intelligence (AI) model is divided between the edge and the cloud, with intermediate features being sent from the edge to the cloud for inference.
UAV-enabled Collaborative Beamforming via Multi-Agent Deep Reinforcement Learning
To improve the work efficiency of the UVAA, we formulate a UAV-enabled collaborative beamforming multi-objective optimization problem (UCBMOP) to simultaneously maximize the transmission rate of the UVAA and minimize the energy consumption of all UAVs by optimizing the positions and excitation current weights of all UAVs.
Collaborative Ground-Space Communications via Evolutionary Multi-objective Deep Reinforcement Learning
Specifically, it is found that DCB enables terminals that cannot reach the uplink achievable threshold to achieve efficient direct uplink transmission, which thus reveals that DCB is an effective solution for enabling direct ground-space communications.
