Plug and Play Labeling Strategies for Boosting Small Brain Lesion Segmentation [0.03%]
用于增强小脑病变分割的即插即用标签策略
Liang Shang,Zhengyang Lou,William Sethares et al.
Liang Shang et al.
Accurate segmentation of small brain lesions in magnetic resonance imaging (MRI) is essential for understanding neurological disorders and guiding clinical decisions. However, detecting small lesions remains challenging due to low contrast ...
MedLesSynth-LD: Lesion synthesis using physics-based noise models for robust lesion segmentation in low-data medical imaging regimes [0.03%]
基于物理的噪声模型的医学图像病变合成方法用于数据不足条件下的鲁棒性病变更分段任务
Ramanujam Narayanan,Vaanathi Sundaresan
Ramanujam Narayanan
Training models for robust lesion segmentation in medical imaging relies on the availability of sufficiently large pathological datasets and high-quality manual annotations. Hence, training such models is challenging in low-data regimes, ev...
Saurabh Hinduja,Tara Nourivandi,Jeffrey F Cohn et al.
Saurabh Hinduja et al.
Detecting action units is an important task in face analysis, especially in facial expression recognition. This is due, in part, to the idea that expressions can be decomposed into multiple action units. To evaluate systems that detect acti...
Jingyan Xu
Jingyan Xu
The area under the Receiver Operating Characteristic (ROC) curve (AUC) is a standard metric for quantifying and comparing binary classifiers. A popular approach to estimating the AUCs and the associated variabilities - the variance of the A...
Nikolay Dagaev,Brett D Roads,Xiaoliang Luo et al.
Nikolay Dagaev et al.
Despite their impressive performance in object recognition and other tasks under standard testing conditions, deep networks often fail to generalize to out-of-distribution (o.o.d.) samples. One cause for this shortcoming is that modern arch...
Brian Ondov,Hanan Samet
Brian Ondov
Region expansion-the growth of regions to include all points within a certain distance of their perimeters-is a basic, widely applicable operation, but is expensive to perform exactly. It has been shown that, if the solution is approximated...
Face-mask-aware Facial Expression Recognition based on Face Parsing and Vision Transformer [0.03%]
基于面部解析和视觉变换器的戴口罩面部表情识别
Bo Yang,Jianming Wu,Kazushi Ikeda et al.
Bo Yang et al.
As wearing face masks is becoming an embedded practice due to the COVID-19 pandemic, facial expression recognition (FER) that takes face masks into account is now a problem that needs to be solved. In this paper, we propose a face parsing a...
ETCNN: Extra Tree and Convolutional Neural Network-based Ensemble Model for COVID-19 Tweets Sentiment Classification [0.03%]
用于COVID-19推文情感分类的基于额外树和卷积神经网络的集成模型ETCNN
Muhammad Umer,Saima Sadiq,Hanen Karamti et al.
Muhammad Umer et al.
Pandemics influence people negatively and people experience fear and disappointment. With the global outspread of COVID-19, the sentiments of the general public are substantially influenced, and analyzing their sentiments could help to devi...
Characterizing pandemic waves: A latent class analysis of COVID-19 spread across US counties [0.03%]
美国各县COVID-19传播特征分析：潜在类别方法区分疫情发展阶段
Md Yusuf Sarwar Uddin,Rezwana Rafiq
Md Yusuf Sarwar Uddin
The spread of the COVID-19 pandemic is observed to follow the shape of "waves" (i.e., the rise and fall of population-adjusted daily new infection cases with time). Different geographic regions of the world have experienced different positi...
A Discriminative Channel Diversification Network for Image Classification [0.03%]
一种 discriminative channel diversification网络的图像分类方法
Krushi Patel,Guanghui Wang
Krushi Patel
Channel attention mechanisms in convolutional neural networks have been proven to be effective in various computer vision tasks. However, the performance improvement comes with additional model complexity and computation cost. In this paper...