Results 1 to 10 of about 5,333 (115)

Multi-Stage Multi-Scale Local Feature Fusion for Infrared Small Target Detection

Remote Sensing, 2023
The detection of small infrared targets with dense distributions and large-scale variations is an extremely challenging problem. This paper proposes a multi-stage, multi-scale local feature fusion method for infrared small target detection to address ...
Yahui Wang, , Jijun Liu
exaly   +3 more sources

Face Verification with Multi-Task and Multi-Scale Features Fusion [PDF]

Entropy, 2017
Face verification for unrestricted faces in the wild is a challenging task. This paper proposes a method based on two deep convolutional neural networks(CNN) for face verification. In this work, we explore to use identification signal to supervise one CNN and the combination of semi-verification and identification to train the other one.
Xiaojun Lu, Yue Yang, Weilin Zhang, Qi Wang 0003, Yang Wang   +4 more
openaire   +4 more sources

Multi-Scale Feature Interactive Fusion Network for RGBT Tracking

Sensors, 2023
The fusion tracking of RGB and thermal infrared image (RGBT) is paid wide attention to due to their complementary advantages. Currently, most algorithms obtain modality weights through attention mechanisms to integrate multi-modalities information. They do not fully exploit the multi-scale information and ignore the rich contextual information among ...
Xianbing Xiao, Xingzhong Xiong, Fanqin Meng, Zhen Chen   +3 more
openaire   +4 more sources

MSLF-Net: A Multi-Scale and Multi-Level Feature Fusion Net for Diabetic Retinopathy Segmentation

Diagnostics, 2022
Diabetic Retinopathy (DR) is a diabetic complication that predisposes patients to visual impairments that could lead to blindness. Lesion segmentation using deep learning algorithms is an effective measure to screen and prevent early DR.
Jiexin Xie, Shijie Guo, Guo Shijie
exaly   +3 more sources

SSD with multi-scale feature fusion and attention mechanism

Scientific Reports, 2022
Abstract In the field of the Internet of Things, image acquisition equipment is the very important equipment, which will generate lots of invalid data during real-time monitoring. Analyzing the data collected directly from the terminal by edge calculation, we can remove invalid frames and improve the accuracy of system detection.
Qiang Liu, Lijun Dong, Zhigao Zeng, Wenqiu Zhu, Yanhui Zhu, Chen Meng   +5 more
openaire   +3 more sources

Revisiting Multi-Scale Feature Fusion for Semantic Segmentation

CoRR, 2022
It is commonly believed that high internal resolution combined with expensive operations (e.g. atrous convolutions) are necessary for accurate semantic segmentation, resulting in slow speed and large memory usage. In this paper, we question this belief and demonstrate that neither high internal resolution nor atrous convolutions are necessary.
Tianjian Meng, Golnaz Ghiasi, Reza Mahjourian, Quoc V. Le, Mingxing Tan   +4 more
openaire   +2 more sources

EEG Emotion Recognition by Fusion of Multi-Scale Features

Brain Sciences, 2023
Electroencephalogram (EEG) signals exhibit low amplitude, complex background noise, randomness, and significant inter-individual differences, which pose challenges in extracting sufficient features and can lead to information loss during the mapping process from low-dimensional feature matrices to high-dimensional ones in emotion recognition algorithms.
Xiuli Du, Yifei Meng, Shaoming Qiu, Yana Lv, Qingli Liu   +4 more
openaire   +3 more sources

Multi-Scale Boosted Dehazing Network With Dense Feature Fusion [PDF]

2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020
In this paper, we propose a Multi-Scale Boosted Dehazing Network with Dense Feature Fusion based on the U-Net architecture. The proposed method is designed based on two principles, boosting and error feedback, and we show that they are suitable for the dehazing problem.
Hang Dong 0001, Jinshan Pan, Lei Xiang, Zhe Hu, Xinyi Zhang 0005, Fei Wang 0008, Ming-Hsuan Yang 0001   +6 more
openaire   +2 more sources

Attention‐based multi‐scale feature fusion for free‐space detection

IET Intelligent Transport Systems, 2022
Free space detection is a very important task in road scene understanding. With the continued development of convolutional neural networks, free‐space detection can be seen as a class‐specific semantic segmentation problem.
Pengfei Song, Hui Fan, Jinjiang Li, Feng Hua   +3 more
doaj   +1 more source

Scene Uyghur Text Detection Based on Fine-Grained Feature Representation

Sensors, 2022
Scene text detection task aims to precisely localize text in natural environments. At present, the application scenarios of text detection topics have gradually shifted from plain document text to more complex natural scenarios.
Yiwen Wang, Hornisa Mamat, Xuebin Xu, Alimjan Aysa, Kurban Ubul   +4 more
doaj   +1 more source