53 Result(s)
within
Chapter
Minghui **ao
Image Processing and Computer Vision
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Chapter and Conference Paper
AgsNet: An Attention-Guided Lightweight Segmentation Network
Urinalysis test strips are commonly used for urine routine examination. However, due to possible defects in the liquid path, such as blockages, droplets may leak during the process of drop** urine samples on...
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Chapter and Conference Paper
HuMoMM: A Multi-Modal Dataset and Benchmark for Human Motion Analysis
Human motion analysis is a fundamental task in computer vision, and there is an increasing demand for versatile datasets with the development of deep learning. However, how to obtain the annotations of human m...
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Chapter and Conference Paper
The Transition Law of Sepsis Patients’ Illness States Based on Complex Network
Sepsis is a disease with a high mortality rate of 15%–50%. It is of great significance to study disease development rules of sepsis patients, which can summarize the clinical pattern and provide support for cl...
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Chapter and Conference Paper
Correction to: Weakly Supervised Whole Cardiac Segmentation via Attentional CNN
In the originally published version of chapter 9, by error, the author **ye Peng had been assigned affiliation no. “3” instead of “2”. This has been corrected.
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Chapter and Conference Paper
Weakly Supervised Whole Cardiac Segmentation via Attentional CNN
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Chapter and Conference Paper
Interpretable Lung Cancer Diagnosis with Nodule Attribute Guidance and Online Model Debugging
Accurate nodule labeling and interpretable machine learning are important for lung cancer diagnosis. To circumvent the label ambiguity issue of commonly-used unsure nodule data such as LIDC-IDRI, we constructe...
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Chapter and Conference Paper
Lane Detection Transformer Based on Multi-frame Horizontal and Vertical Attention and Visual Transformer Module
Lane detection requires adequate global information due to the simplicity of lane line features and changeable road scenes. In this paper, we propose a novel lane detection Transformer based on multi-frame inp...
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Chapter and Conference Paper
Density-NMS: Cell Detection and Classification in Microscopy Images
With the development of digital pathology, the automatic detection and classification of microscopy image cells using artificial intelligence technology has become a research hotspot. However, due to the probl...
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Chapter and Conference Paper
An Outdoor Navigation System for Mobile Robots Based on Human Detection
The reliable navigation of mobile robots outdoors depends on high-precision maps, accurate localization and efficient path planning. The complexity and variability of outdoor scenes bring great challenges to t...
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Chapter and Conference Paper
Single Image Specular Highlight Removal on Natural Scenes
Previous methods of highlight removal in image processing have exclusively addressed images taken in specific illumination environments. However, most of these methods have limitations in natural scenes and th...
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Chapter and Conference Paper
FDA: Feature Decomposition and Aggregation for Robust Airway Segmentation
3D Convolutional Neural Networks (CNNs) have been widely adopted for airway segmentation. The performance of 3D CNNs is greatly influenced by the dataset while the public airway datasets are mainly clean CT sc...
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Chapter and Conference Paper
Color Recognition Method Based on Image Segmentation
In this paper, we present a color recognition method that conforms to the color perception of human eyes in order to realize the recognition of the bleeding position of the human body through RGB image. The HS...
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Chapter and Conference Paper
Instance-Aware Feature Alignment for Cross-Domain Cell Nuclei Detection in Histopathology Images
Robust nuclei detection is crucial prerequisite for histologic characteristics of nuclei that can assist various clinical tasks such as disease diagnosis and cancer grading. Despite of their success, most exis...
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Chapter and Conference Paper
Effect of Postures and Cutting Process on Robot Milling Performance and Surface Quality
The application of industrial robots in machining fields is of great significance to the integral machining of large complex structures. However, subject to the structural rigidity, it can not become the mains...
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Chapter and Conference Paper
Online Object-Oriented Semantic Map** in Triger Classification Environment
Creating and maintaining an accurate representation of the environment is an essential capability for every mobile robot. Especially, semantic information plays an important role in mobile robot navigation and...
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Chapter and Conference Paper
TransPath: Transformer-Based Self-supervised Learning for Histopathological Image Classification
A large-scale labeled dataset is a key factor for the success of supervised deep learning in histopathological image analysis. However, exhaustive annotation requires a careful visual inspection by pathologist...
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Chapter and Conference Paper
Improved 3D Morphable Model for Facial Action Unit Synthesis
To overcome the limitation of the conventional 3D face model on the synthesis of local facial expression movements, this paper proposes an improved 3D face model that combines facial action coding system (FACS...
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Chapter and Conference Paper
Artificial Intelligence for Prosthetics: Challenge Solutions
In the NeurIPS 2018 Artificial Intelligence for Prosthetics challenge, participants were tasked with building a controller for a musculoskeletal model with a goal of matching a given time-varying velocity vector....
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Chapter and Conference Paper
Mask TextSpotter v3: Segmentation Proposal Network for Robust Scene Text Spotting
Recent end-to-end trainable methods for scene text spotting, integrating detection and recognition, showed much progress. However, most of the current arbitrary-shape scene text spotters use region proposal ne...
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Chapter and Conference Paper
Self-Prediction for Joint Instance and Semantic Segmentation of Point Clouds
We develop a novel learning scheme named Self-Prediction for 3D instance and semantic segmentation of point clouds. Distinct from most existing methods that focus on designing convolutional operators, our meth...
