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Found 57 papers, 13 papers with code
Intra-class Feature Variation Distillation for Semantic Segmentation
In this paper, different from previous methods performing knowledge distillation for densely pairwise relations, we propose a novel intra-class feature variation distillation (IFVD) to transfer the intra-class feature variation (IFV) of the cumbersome model (teacher) to the compact model (student).
Robust Multi-agent Communication via Multi-view Message Certification
Many multi-agent scenarios require message sharing among agents to promote coordination, hastening the robustness of multi-agent communication when policies are deployed in a message perturbation environment.
Occ3D: A Large-Scale 3D Occupancy Prediction Benchmark for Autonomous Driving
To overcome these limitations, we introduce a novel task for 3D occupancy prediction, which aims to estimate the detailed occupancy and semantics of objects from multi-view images.
Taking A Closer Look at Visual Relation: Unbiased Video Scene Graph Generation with Decoupled Label Learning
Specifically, DLL decouples the predicate labels and adopts separate classifiers to learn actional and spatial patterns respectively.
RTMPose: Real-Time Multi-Person Pose Estimation based on MMPose
Recent studies on 2D pose estimation have achieved excellent performance on public benchmarks, yet its application in the industrial community still suffers from heavy model parameters and high latency.
Ranked #1 on
2D Human Pose Estimation
on COCO-WholeBody
Re-embedding data to strengthen recovery guarantees of clustering
We propose a clustering method that involves chaining four known techniques into a pipeline yielding an algorithm with stronger recovery guarantees than any of the four components separately.
Towards A Unified Conformer Structure: from ASR to ASV Task
Transformer has achieved extraordinary performance in Natural Language Processing and Computer Vision tasks thanks to its powerful self-attention mechanism, and its variant Conformer has become a state-of-the-art architecture in the field of Automatic Speech Recognition (ASR).
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
S3E: A Large-scale Multimodal Dataset for Collaborative SLAM
With the advanced request to employ a team of robots to perform a task collaboratively, the research community has become increasingly interested in collaborative simultaneous localization and mapping.
Stochastic Variational Methods in Generalized Hidden Semi-Markov Models to Characterize Functionality in Random Heteropolymers
Recent years have seen substantial advances in the development of biofunctional materials using synthetic polymers.
CVM-Cervix: A Hybrid Cervical Pap-Smear Image Classification Framework Using CNN, Visual Transformer and Multilayer Perceptron
Cervical cytopathology image classification is an important method to diagnose cervical cancer.
Exploring Diversity-based Active Learning for 3D Object Detection in Autonomous Driving
3D object detection has recently received much attention due to its great potential in autonomous vehicle (AV).
Learning Based User Scheduling in Reconfigurable Intelligent Surface Assisted Multiuser Downlink
Reconfigurable intelligent surface (RIS) is capable of intelligently manipulating the phases of the incident electromagnetic wave to improve the wireless propagation environment between the base-station (BS) and the users.
An application of Pixel Interval Down-sampling (PID) for dense tiny microorganism counting on environmental microorganism images
This paper proposes a novel pixel interval down-sampling network (PID-Net) for dense tiny object (yeast cells) counting tasks with higher accuracy.
Acceleration of Federated Learning with Alleviated Forgetting in Local Training
Here, we propose FedReg, an algorithm to accelerate FL with alleviated knowledge forgetting in the local training stage by regularizing locally trained parameters with the loss on generated pseudo data, which encode the knowledge of previous training data learned by the global model.
A Comprehensive Survey with Quantitative Comparison of Image Analysis Methods for Microorganism Biovolume Measurements
This study has high research significance and application value, which can be referred to microbial researchers to have a comprehensive understanding of microorganism biovolume measurements using digital image analysis methods and potential applications.
A Survey of Semen Quality Evaluation in Microscopic Videos Using Computer Assisted Sperm Analysis
The various works related to Computer Assisted Sperm Analysis methods in the last 30 years (since 1988) are comprehensively introduced and analysed in this survey.
A State-of-the-art Survey of U-Net in Microscopic Image Analysis: from Simple Usage to Structure Mortification
Image analysis technology is used to solve the inadvertences of artificial traditional methods in disease, wastewater treatment, environmental change monitoring analysis and convolutional neural networks (CNN) play an important role in microscopic image analysis.
Forgery Attack Detection in Surveillance Video Streams Using Wi-Fi Channel State Information
The cybersecurity breaches expose surveillance video streams to forgery attacks, under which authentic streams are falsified to hide unauthorized activities.
EMDS-6: Environmental Microorganism Image Dataset Sixth Version for Image Denoising, Segmentation, Feature Extraction, Classification and Detection Methods Evaluation
Each type of EM contains 40 original and 40 GT images, in total 1680 EM images.
Active Sensing for Communications by Learning
This paper proposes a deep learning approach to a class of active sensing problems in wireless communications in which an agent sequentially interacts with an environment over a predetermined number of time frames to gather information in order to perform a sensing or actuation task for maximizing some utility function.
EMDS-7: Environmental Microorganism Image Dataset Seventh Version for Multiple Object Detection Evaluation
The Environmental Microorganism Image Dataset Seventh Version (EMDS-7) is a microscopic image data set, including the original Environmental Microorganism images (EMs) and the corresponding object labeling files in ". XML" format file.
Looking for the Signs: Identifying Isolated Sign Instances in Continuous Video Footage
In this paper, we focus on the task of one-shot sign spotting, i. e. given an example of an isolated sign (query), we want to identify whether/where this sign appears in a continuous, co-articulated sign language video (target).
A Comparative Study of Deep Learning Classification Methods on a Small Environmental Microorganism Image Dataset (EMDS-6): from Convolutional Neural Networks to Visual Transformers
In recent years, deep learning has made brilliant achievements in Environmental Microorganism (EM) image classification.
A Comparison for Patch-level Classification of Deep Learning Methods on Transparent Environmental Microorganism Images: from Convolutional Neural Networks to Visual Transformers
We conclude that ViT performs the worst in classifying 8 * 8 pixel patches, but it outperforms most convolutional neural networks in classifying 224 * 224 pixel patches.
Is the aspect ratio of cells important in deep learning? A robust comparison of deep learning methods for multi-scale cytopathology cell image classification: from convolutional neural networks to visual transformers
The results of the study indicate that deep learning models are robust to changes in the aspect ratio of cells in cervical cytopathological images.
Skeletor: Skeletal Transformers for Robust Body-Pose Estimation
Skeletor can achieve this as it implicitly learns the spatio-temporal context of human motion via a transformer based neural network.
Evaluating the Immediate Applicability of Pose Estimation for Sign Language Recognition
Basically, skeletal representations generalize over an individual's appearance and background, allowing us to focus on the recognition of motion.
A State-of-the-art Survey of Artificial Neural Networks for Whole-slide Image Analysis:from Popular Convolutional Neural Networks to Potential Visual Transformers
Finally, the application prospect of the analytical method in this field is discussed.
A Comprehensive Review of Image Analysis Methods for Microorganism Counting: From Classical Image Processing to Deep Learning Approaches
In this article, we have studied the development of microorganism counting methods using digital image analysis.
A New Pairwise Deep Learning Feature For Environmental Microorganism Image Analysis
In order to fasten, low the cost, increase consistency and accuracy of identification, we propose the novel pairwise deep learning features to analyze microorganisms.
A Hierarchical Conditional Random Field-based Attention Mechanism Approach for Gastric Histopathology Image Classification
The HCRF-AM model consists of an Attention Mechanism (AM) module and an Image Classification (IC) module.
Policy-Aware Mobility Model Explains the Growth of COVID-19 in Cities
With the continued spread of coronavirus, the task of forecasting distinctive COVID-19 growth curves in different cities, which remain inadequately explained by standard epidemiological models, is critical for medical supply and treatment.
EMDS-5: Environmental Microorganism Image Dataset Fifth Version for Multiple Image Analysis Tasks
EMDS-5 can realize to evaluate image preprocessing, image segmentation, feature extraction, image classification and image retrieval functions.
Towards Cross-Modal Forgery Detection and Localization on Live Surveillance Videos
Traditional video forensics approaches can detect and localize forgery traces in each video frame using computationally-expensive spatial-temporal analysis, while falling short in real-time verification of live video feeds.
Time Series Analysis
Video Forensics
Cryptography and Security
Sparse Coding-inspired GAN for Weakly Supervised Hyperspectral Anomaly Detection
For solving these problems, this paper proposes a sparse coding-inspired generative adversarial network (GAN) for weakly supervised HAD, named sparseHAD.
Peer-to-Peer Localization for Single-Antenna Devices
In this paper, we present P2PLocate, a peer-to-peer localization system that enables a single-antenna device co-located with a batteryless backscatter tag to localize another single-antenna device with decimeter-level accuracy.
Reinforced Molecular Optimization with Neighborhood-Controlled Grammars
A major challenge in the pharmaceutical industry is to design novel molecules with specific desired properties, especially when the property evaluation is costly.
Ranked #1 on
Molecular Graph Generation
on ZINC
(QED Top-3 metric)
Learning to Reflect and to Beamform for Intelligent Reflecting Surface with Implicit Channel Estimation
Intelligent reflecting surface (IRS), which consists of a large number of tunable reflective elements, is capable of enhancing the wireless propagation environment in a cellular network by intelligently reflecting the electromagnetic waves from the base-station (BS) toward the users.
A Review of Deep Reinforcement Learning for Smart Building Energy Management
However, it is a nontrivial task due to the following challenges.
Multi-Agent Deep Reinforcement Learning for HVAC Control in Commercial Buildings
In this paper, we intend to minimize the energy cost of an HVAC system in a multi-zone commercial building under dynamic pricing with the consideration of random zone occupancy, thermal comfort, and indoor air quality comfort.
Certifying clusters from sum-of-norms clustering
Multiple algorithms have been proposed to solve the optimization problem: subgradient descent by Hocking et al., ADMM and ADA by Chi and Lange, stochastic incremental algorithm by Panahi et al. and semismooth Newton-CG augmented Lagrangian method by Sun et al. All algorithms yield approximate solutions, even though an exact solution is demanded to determine the correct cluster assignment.
Robot-assisted Backscatter Localization for IoT Applications
Recent years have witnessed the rapid proliferation of backscatter technologies that realize the ubiquitous and long-term connectivity to empower smart cities and smart homes.
A Comprehensive Review for Breast Histopathology Image Analysis Using Classical and Deep Neural Networks
Breast cancer is one of the most common and deadliest cancers among women.
Edge Intelligence: Architectures, Challenges, and Applications
Edge intelligence refers to a set of connected systems and devices for data collection, caching, processing, and analysis in locations close to where data is captured based on artificial intelligence.
A Multi-scale CNN-CRF Framework for Environmental Microorganism Image Segmentation
In order to assist researchers to identify Environmental Microorganisms (EMs) effectively, a Multi-scale CNN-CRF (MSCC) framework for the EM image segmentation is proposed in this paper.
Gastric histopathology image segmentation using a hierarchical conditional random field
This HCRF model is built up with higher order potentials, including pixel-level and patch-level potentials, and graph-based post-processing is applied to further improve its segmentation performance.
Communication-Efficient Edge AI: Algorithms and Systems
By pushing inference and training processes of AI models to edge nodes, edge AI has emerged as a promising alternative.
Utilizing BERT Intermediate Layers for Aspect Based Sentiment Analysis and Natural Language Inference
Aspect based sentiment analysis aims to identify the sentimental tendency towards a given aspect in text.
Aspect-Based Sentiment Analysis (ABSA)
Natural Language Inference
VerSe: A Vertebrae Labelling and Segmentation Benchmark for Multi-detector CT Images
Two datasets containing a total of 374 multi-detector CT scans from 355 patients were prepared and 4505 vertebrae have individually been annotated at voxel-level by a human-machine hybrid algorithm (https://osf. io/nqjyw/, https://osf. io/t98fz/).
Sensor-Augmented Neural Adaptive Bitrate Video Streaming on UAVs
In this paper, we present SA-ABR, a new sensor-augmented system that generates ABR video streaming algorithms with the assistance of various kinds of inherent sensor data that are used to pilot UAVs.
Automated Steel Bar Counting and Center Localization with Convolutional Neural Networks
The proposed CNN-DC can achieve 99. 26% accuracy for steel bar counting and 4. 1% center offset for center localization on the established steel bar dataset, which demonstrates that the proposed CNN-DC can perform well on automated steel bar counting and center localization.
Attentional Encoder Network for Targeted Sentiment Classification
Most of the previous approaches model context and target words with RNN and attention.
Ranked #1 on
Sentiment Analysis
on Twitter
Recovery of a mixture of Gaussians by sum-of-norms clustering
Sum-of-norms clustering is a method for assigning $n$ points in $\mathbb{R}^d$ to $K$ clusters, $1\le K\le n$, using convex optimization.
Federated Learning via Over-the-Air Computation
Instead, edge machine learning becomes increasingly attractive for performing training and inference directly at network edges without sending data to a centralized data center.
Double Neural Counterfactual Regret Minimization
Counterfactual Regret Minimization (CRF) is a fundamental and effective technique for solving Imperfect Information Games (IIG).
Cross-Technology Communications for Heterogeneous IoT Devices Through Artificial Doppler Shifts
To this end, we propose DopplerFi, a communication framework that enables a two-way communication channel between BLE and Wi-Fi by injecting artificial Doppler shifts, which can be decoded by sensing the patterns in the Gaussian frequency shift keying (GFSK) demodulator and Channel State Information (CSI).
Networking and Internet Architecture
Distributed Private Online Learning for Social Big Data Computing over Data Center Networks
An increasing number of people participate in social networks and massive online social data are obtained.
