Search Results for author:
Found 31 papers, 5 papers with code
An Improved Lightweight YOLOv5 Model Based on Attention Mechanism for Face Mask Detection
However, existing deep learning based models struggle to simultaneously achieve the requirements of both high precision and real-time performance.
TransCG: A Large-Scale Real-World Dataset for Transparent Object Depth Completion and Grasping
However, the majority of current grasping algorithms would fail in this case since they heavily rely on the depth image, while ordinary depth sensors usually fail to produce accurate depth information for transparent objects owing to the reflection and refraction of light.
Ranked #1 on
Transparent Object Depth Estimation
on TransCG
TerViT: An Efficient Ternary Vision Transformer
Vision transformers (ViTs) have demonstrated great potential in various visual tasks, but suffer from expensive computational and memory cost problems when deployed on resource-constrained devices.
Neural Content Extraction for Poster Generation of Scientific Papers
Then we propose a three-step framework to tackle this task and focus on the content extraction step in this study.
POEM: 1-bit Point-wise Operations based on Expectation-Maximization for Efficient Point Cloud Processing
Real-time point cloud processing is fundamental for lots of computer vision tasks, while still challenged by the computational problem on resource-limited edge devices.
Collage: Automated Integration of Deep Learning Backends
Strong demands for efficient deployment of Deep Learning (DL) applications prompt the rapid development of a rich DL ecosystem.
End-to-end Ultrasound Frame to Volume Registration
Fusing intra-operative 2D transrectal ultrasound (TRUS) image with pre-operative 3D magnetic resonance (MR) volume to guide prostate biopsy can significantly increase the yield.
Cross-modal Attention for MRI and Ultrasound Volume Registration
In the past few years, convolutional neural networks (CNNs) have been proved powerful in extracting image features crucial for image registration.
Layer-Wise Searching for 1-Bit Detectors
At each layer, it exploits a differentiable binarization search (DBS) to minimize the angular error in a student-teacher framework.
RGB Matters: Learning 7-DoF Grasp Poses on Monocular RGBD Images
In the first stage, an encoder-decoder like convolutional neural network Angle-View Net(AVN) is proposed to predict the SO(3) orientation of the gripper at every location of the image.
FlashP: An Analytical Pipeline for Real-time Forecasting of Time-Series Relational Data
Our scalable real-time forecasting system FlashP (Flash Prediction) is built based on this idea, with two major challenges to be resolved in this paper: first, we need to figure out how approximate aggregations affect the fitting of forecasting models, and forecasting results; and second, accordingly, what sampling algorithms we should use to obtain these approximate aggregations and how large the samples are.
A Neural Local Coherence Analysis Model for Clarity Text Scoring
Local coherence relation between two phrases/sentences such as cause-effect and contrast gives a strong influence of whether a text is well-structured or not.
Federated Semi-Supervised Learning for COVID Region Segmentation in Chest CT using Multi-National Data from China, Italy, Japan
To facilitate CT analysis, recent efforts have focused on computer-aided characterization and diagnosis, which has shown promising results.
Transducer Adaptive Ultrasound Volume Reconstruction
However, such algorithms are specific to particular transducers and scanning trajectories associated with the training data, which may not be generalized to other image acquisition settings.
Deep Neural Tangent Kernel and Laplace Kernel Have the Same RKHS
We prove that the reproducing kernel Hilbert spaces (RKHS) of a deep neural tangent kernel and the Laplace kernel include the same set of functions, when both kernels are restricted to the sphere $\mathbb{S}^{d-1}$.
The 1st Tiny Object Detection Challenge:Methods and Results
The 1st Tiny Object Detection (TOD) Challenge aims to encourage research in developing novel and accurate methods for tiny object detection in images which have wide views, with a current focus on tiny person detection.
Two-Stage Maximum Score Estimator
We characterize the asymptotic distribution of the TSMS estimator, which features phase transitions depending on the dimension and thus the convergence rate of the first-stage estimation.
Sensorless Freehand 3D Ultrasound Reconstruction via Deep Contextual Learning
Transrectal ultrasound (US) is the most commonly used imaging modality to guide prostate biopsy and its 3D volume provides even richer context information.
Tree-Projected Gradient Descent for Estimating Gradient-Sparse Parameters on Graphs
We study estimation of a gradient-sparse parameter vector $\boldsymbol{\theta}^* \in \mathbb{R}^p$, having strong gradient-sparsity $s^*:=\|\nabla_G \boldsymbol{\theta}^*\|_0$ on an underlying graph $G$.
Logical Differencing in Dyadic Network Formation Models with Nontransferable Utilities
This paper considers a semiparametric model of dyadic network formation under nontransferable utilities (NTU).
Unified Multi-scale Feature Abstraction for Medical Image Segmentation
Automatic medical image segmentation, an essential component of medical image analysis, plays an importantrole in computer-aided diagnosis.
Topic Tensor Network for Implicit Discourse Relation Recognition in Chinese
In the literature, most of the previous studies on English implicit discourse relation recognition only use sentence-level representations, which cannot provide enough semantic information in Chinese due to its unique paratactic characteristics.
Iterative Alpha Expansion for estimating gradient-sparse signals from linear measurements
We consider estimating a piecewise-constant image, or a gradient-sparse signal on a general graph, from noisy linear measurements.
Shubnikov-de Haas and de Haas-van Alphen oscillations in topological semimetal CaAl4
An electron-type quasi-2D Fermi surface is found by the angle-dependent Shubnikov-de Haas oscillations, de Haas-van Alphen oscillations and the first-principles calculations.
Materials Science Mesoscale and Nanoscale Physics
Employing Text Matching Network to Recognise Nuclearity in Chinese Discourse
The task of nuclearity recognition in Chinese discourse remains challenging due to the demand for more deep semantic information.
MCDTB: A Macro-level Chinese Discourse TreeBank
In view of the differences between the annotations of micro and macro discourse rela-tionships, this paper describes the relevant experiments on the construction of the Macro Chinese Discourse Treebank (MCDTB), a higher-level Chinese discourse corpus.
Learning Deep Similarity Metric for 3D MR-TRUS Registration
Conclusion: A similarity metric that is learned using a deep neural network can be used to assess the quality of any given image registration and can be used in conjunction with the aforementioned optimization framework to perform automatic registration that is robust to poor initialization.
Adversarial Image Registration with Application for MR and TRUS Image Fusion
Robust and accurate alignment of multimodal medical images is a very challenging task, which however is very useful for many clinical applications.
An optimal hierarchical clustering approach to segmentation of mobile LiDAR point clouds
The main contribution of this paper is that we succeed to optimize the combination of clusters in the hierarchical clustering.
Road Curb Extraction from Mobile LiDAR Point Clouds
Automatic extraction of road curbs from uneven, unorganized, noisy and massive 3D point clouds is a challenging task.
