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SpecTr: Spectral Transformer for Hyperspectral Pathology Image Segmentation
Hyperspectral imaging (HSI) unlocks the huge potential to a wide variety...
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Batch Normalization with Enhanced Linear Transformation
Batch normalization (BN) is a fundamental unit in modern deep networks, ...
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Volumetric Medical Image Segmentation: A 3D Deep Coarse-to-fine Framework and Its Adversarial Examples
Although deep neural networks have been a dominant method for many 2D vi...
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AutoADR: Automatic Model Design for Ad Relevance
Large-scale pre-trained models have attracted extensive attention in the...
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Shape-Texture Debiased Neural Network Training
Shape and texture are two prominent and complementary cues for recognizi...
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CO2: Consistent Contrast for Unsupervised Visual Representation Learning
Contrastive learning has been adopted as a core method for unsupervised ...
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Auxiliary-task Based Deep Reinforcement Learning for Participant Selection Problem in Mobile Crowdsourcing
In mobile crowdsourcing (MCS), the platform selects participants to comp...
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Towards Unsupervised Learning for Instrument Segmentation in Robotic Surgery with Cycle-Consistent Adversarial Networks
Surgical tool segmentation in endoscopic images is an important problem:...
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Domain Adaptive Relational Reasoning for 3D Multi-Organ Segmentation
In this paper, we present a novel unsupervised domain adaptation (UDA) m...
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Segmentation for Classification of Screening Pancreatic Neuroendocrine Tumors
This work presents comprehensive results to detect in the early stage th...
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Detecting Pancreatic Adenocarcinoma in Multi-phase CT Scans via Alignment Ensemble
Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancer...
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Synthesize then Compare: Detecting Failures and Anomalies for Semantic Segmentation
The ability to detect failures and anomalies are fundamental requirement...
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Deep Distance Transform for Tubular Structure Segmentation in CT Scans
Tubular structure segmentation in medical images, e.g., segmenting vesse...
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Shape-aware Feature Extraction for Instance Segmentation
Modern instance segmentation approaches mainly adopt a sequential paradi...
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Rethinking Normalization and Elimination Singularity in Neural Networks
In this paper, we study normalization methods for neural networks from t...
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TDAPNet: Prototype Network with Recurrent Top-Down Attention for Robust Object Classification under Partial Occlusion
Despite deep convolutional neural networks' great success in object clas...
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Deep Differentiable Random Forests for Age Estimation
Age estimation from facial images is typically cast as a label distribut...
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Learning to Find Correlated Features by Maximizing Information Flow in Convolutional Neural Networks
Training convolutional neural networks for image classification tasks us...
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Stability and Optimization Error of Stochastic Gradient Descent for Pairwise Learning
In this paper we study the stability and its trade-off with optimization...
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Weight Standardization
In this paper, we propose Weight Standardization (WS) to accelerate deep...
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Learning from Adversarial Features for Few-Shot Classification
Many recent few-shot learning methods concentrate on designing novel mod...
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Learning to generate filters for convolutional neural networks
Conventionally, convolutional neural networks (CNNs) process different i...
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Robust Face Detection via Learning Small Faces on Hard Images
Recent anchor-based deep face detectors have achieved promising performa...
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Tackling Early Sparse Gradients in Softmax Activation Using Leaky Squared Euclidean Distance
Softmax activation is commonly used to output the probability distributi...
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Generating Attention from Classifier Activations for Fine-grained Recognition
Recent advances in fine-grained recognition utilize attention maps to lo...
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PCL: Proposal Cluster Learning for Weakly Supervised Object Detection
Weakly Supervised Object Detection (WSOD), using only image-level annota...
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Spatial Transformer Introspective Neural Network
Natural images contain many variations such as illumination differences,...
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Abdominal multi-organ segmentation with organ-attention networks and statistical fusion
Accurate and robust segmentation of abdominal organs on CT is essential ...
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Training Multi-organ Segmentation Networks with Sample Selection by Relaxed Upper Confident Bound
Deep convolutional neural networks (CNNs), especially fully convolutiona...
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Semi-supervised multi-organ segmentation via multi-planar co-training
Multi-organ segmentation is a critical problem in medical image analysis...
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Deep Co-Training for Semi-Supervised Image Recognition
In this paper, we study the problem of semi-supervised image recognition...
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Hi-Fi: Hierarchical Feature Integration for Skeleton Detection
In natural images, skeleton scales (thickness) may significantly vary am...
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Deep Regression Forests for Age Estimation
Age estimation from facial images is typically cast as a nonlinear regre...
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Crack detection in beam structures with a novel Laplace based Wavelet Finite Element method
Beam structure is one of the most widely used structures in mechanical e...
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Wave analysis in one dimensional structures with a wavelet finite element model and precise integration method
Numerical simulation of ultrasonic wave propagation provides an efficien...
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Single-Shot Object Detection with Enriched Semantics
We propose a novel single shot object detection network named Detection ...
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A 3D Coarse-to-Fine Framework for Automatic Pancreas Segmentation
In this paper, we adopt 3D CNNs to segment the pancreas in CT images. Al...
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Gradually Updated Neural Networks for Large-Scale Image Recognition
We present a simple yet effective neural network architecture for image ...
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Few-Shot Image Recognition by Predicting Parameters from Activations
In this paper, we are interested in the few-shot learning problem. In pa...
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Multi-stage Multi-recursive-input Fully Convolutional Networks for Neuronal Boundary Detection
In the field of connectomics, neuroscientists seek to identify cortical ...
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A Fixed-Point Model for Pancreas Segmentation in Abdominal CT Scans
Deep neural networks have been widely adopted for automatic organ segmen...
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Learning Residual Images for Face Attribute Manipulation
Face attributes are interesting due to their detailed description of hum...
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DeepSkeleton: Learning Multi-task Scale-associated Deep Side Outputs for Object Skeleton Extraction in Natural Images
Object skeletons are useful for object representation and object detecti...
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Shape Recognition by Bag of Skeleton-associated Contour Parts
Contour and skeleton are two complementary representations for shape rec...
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Multi-Oriented Text Detection with Fully Convolutional Networks
In this paper, we propose a novel approach for text detec- tion in natur...
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Object Skeleton Extraction in Natural Images by Fusing Scale-associated Deep Side Outputs
Object skeleton is a useful cue for object detection, complementary to t...
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