![Loading...](https://link.springer.com/static/c4a417b97a76cc2980e3c25e2271af3129e08bbe/images/pdf-preview/spacer.gif)
-
Chapter and Conference Paper
A Foreground Feature Embedding Network for Object Detection in Remote Sensing Images
Compared with traditional natural images, remote sensing images (RSIs) typically have high resolution. The objects in the images are densely distributed, with heterogeneous orientation and large scale variatio...
-
Chapter and Conference Paper
TPNet: Enhancing Weakly Supervised Polyp Frame Detection with Temporal Encoder and Prototype-Based Memory Bank
Polyp detection plays a crucial role in the early prevention of colorectal cancer. The availability of large-scale polyp video datasets and video-level annotations has spurred research efforts to formulate pol...
-
Chapter and Conference Paper
A Multi-stage Network with Self-attention for Tooth Instance Segmentation
Automatic and accurate instance segmentation of teeth from 3D Cone-Beam Computer Tomography (CBCT) images is crucial for dental diagnose. Although Convolutional Neural Networks (CNNs) are widely used for tooth...
-
Chapter and Conference Paper
A Classifier-Based Two-Stage Training Model for Few-Shot Segmentation
Over the past few years, deep learning-based semantic segmentation methods reached state-of-the-art performance. The segmentation task is time-consuming and requires a lot of pixel-level annotated data, which ...
-
Chapter and Conference Paper
Detect Any Deepfakes: Segment Anything Meets Face Forgery Detection and Localization
The rapid advancements in computer vision have stimulated remarkable progress in face forgery techniques, capturing the dedicated attention of researchers committed to detecting forgeries and precisely localiz...
-
Chapter and Conference Paper
A Improved Prior Box Generation Method for Small Object Detection
As a task in object detection, small object detection mainly focuses on detecting objects of small size, which is more complex than general object detection. It is pivotal in various applications, e.g., small ...
-
Chapter and Conference Paper
Boundary Difference over Union Loss for Medical Image Segmentation
Medical image segmentation is crucial for clinical diagnosis. However, current losses for medical image segmentation mainly focus on overall segmentation results, with fewer losses proposed to guide boundary s...
-
Chapter and Conference Paper
Generalized Person Re-identification by Locating and Eliminating Domain-Sensitive Features
In this paper, we study the problem of domain generalization for person re-identification (re-ID), which adopts training data from multiple domains to learn a re-ID model that can be directly deployed to unsee...
-
Chapter and Conference Paper
Attention and Multi-granied Feature Learning for Baggage Re-identification
The current baggage re-identification methods only consider the global coarse-grained features while ignoring the fine-grained features. To deal with this issue, we proposed a simple and efficient multi-granul...
-
Chapter and Conference Paper
An Improved SSD-Based Gastric Cancer Detection Method
Gastric cancer is one of the malignant cancers with a very high fatal rate, and early detection plays an essential role in the treatment and improves the five-year 5-year survival rate. In this study, we an im...
-
Chapter and Conference Paper
A Semi-supervised Video Object Segmentation Method Based on Adaptive Memory Module
Video object segmentation has becoming a hot research topic in the computer vision society, with a wide range of applications, such as autonomous driving, video editing, and video surveillance. However, due to...
-
Chapter and Conference Paper
Learning Consistency- and Discrepancy-Context for 2D Organ Segmentation
Recently, CNN-based methods lead tremendous progress in segmenting abdominal organs (e.g., kidney, liver, and pancreas) and anomaly tumors in CT scans. Although 3D CNN-based methods can significantly improve accu...
-
Chapter and Conference Paper
Law Article Prediction via a Codex Enhanced Multi-task Learning Framework
Automatic law article prediction aims to determine appropriate laws for a case by analyzing its corresponding fact description. This research constitutes a relatively new area which has emerged from recommende...
-
Chapter and Conference Paper
A Fast Feature Selection Method Based on Mutual Information in Multi-label Learning
Recently, multi-label learning is concerned and studied in lots of fields by many researchers. However, multi-label datasets often have noisy, irrelevant and redundant features with high dimensionality. Accomp...
-
Chapter and Conference Paper
A Simple and Convex Formulation for Multi-label Feature Selection
In recent years, multi-label study has received extensive attention and research in many fields. The feature dimensions of a multi-label data set are high but contain a large amount of noise as well as irrelev...
-
Chapter and Conference Paper
GridNet with Automatic Shape Prior Registration for Automatic MRI Cardiac Segmentation
In this paper, we propose a fully automatic MRI cardiac segmentation method based on a novel deep convolutional neural network (CNN) designed for the 2017 ACDC MICCAI challenge. The novelty of our network come...