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Optimized Feature Points and Keyframe Methods for VSLAM in High-Dynamic Indoor Environments
Zhuhua Hu;Wenlu Qi;Kunkun Ding;Hao Qi;Yaochi Zhao;Xuebo Zhang;Mingfeng Wang
VSLAM is one of the key technologies for indoor mobile robots, used to perceive the surrounding environment, achieve accurate positioning and mapping. However, traditional VSLAM algorithms based on the assumption of a static environment still face certain challenges. The movement, occlusion, and appearance changes of dynamic objects can lead to feature point-matching errors, making data associatio...Show More
LKPF-YOLO: A Small Target Ship Detection Method for Marine Wide-Area Remote Sensing Images
IEEE Transactions on Aerospace and Electronic Systems
Year: 2024 | Early Access Article |
Ship detection based on wide-area remote sensing imagery has a wide range of applications in areas such as ship supervision and rescue at sea. However, wide-area remote sensing satellites sacrifice spatial resolution and spectral resolution to cover a larger sea area, which leads to smaller ship scales, fewer source pixels, and a lack of texture details in the images. Meanwhile, the sparse distrib...Show More
A Small-Ship Object Detection Method for Satellite Remote Sensing Data
Xiyu Fan;Zhuhua Hu;Yaochi Zhao;Junfei Chen;Tianjiao Wei;Zixun Huang
Satellite remote sensing technology can achieve real-time observation of ships at sea, and the remote sensing images obtained have the advantages of high contrast and low noise and have become one of the important means of marine monitoring. For the satellite remote sensing image data, there are two main problems: first, remote sensing data class-imbalance problem, and second the existing target d...Show More
An Adaptive Lighting Indoor vSLAM With Limited On-Device Resources
IEEE Internet of Things Journal
Cited by: Papers (8)
Visual simultaneous localization and mapping (vSLAM) is a critical technology for enabling robots to achieve self-awareness in unknown environments. However, the robustness and precision of vSLAM are continuously challenged by issues, such as sudden changes in lighting, reflections from shadows, and reduced contrast within indoor settings under constrained hardware resources. This article introduc...Show More
In long-tailed image instance segmentation, the existing methods deal with imbalance problem from a single perspective, which results in the limitation of performance. Considering that imbalances exist not only between positive and negative classes, but also between foreground and background subclasses, as well as between hard and easy examples, we argue that the losses of samples should be hierar...Show More
Balanced RoIMasking for Salient-Instance Segmentation
2023 IEEE 6th International Conference on Pattern Recognition and Artificial Intelligence (PRAI)
Year: 2023 | Conference Paper |
We explore salient-instance segmentation from novel balance perspectives. Salient-instance segmentation includes salient detection and salient segmentation sub-tasks. We focus on the RoIMasking layer in S4Net, which outputs the training data for salient segmentation. Considering the balance between sub-tasks, we propose an expanded smooth RoIMasking (SM) for salient segmentation. SM smooths the tr...Show More
Defense Against Reconstruction Attacks in Split Federated Learning Through Decreasing Correlation Between Inputs and Activations
2023 International Joint Conference on Neural Networks (IJCNN)
Year: 2023 | Conference Paper |
Split Federated Learning (SFL) is the most recent distributed training scheme. Compared to Federated Learning, SFL reduces the overhead of client while achieving better privacy protection. However, SFL attackers can still use the intermediate activations of client to reconstruct the original data containing sensitive information. To defend against this reconstruction attack, we propose to use dist...Show More
TFF_aDCNN: A Pre-Trained Base Model for Intelligent Wideband Spectrum Sensing
In the beyond 5G (B5G)/6G era, to achieve ultra-dense and ultra-large-capacity intelligent connection of all things, an intelligent wideband spectrum sensing technology is particularly important. However, in an extremely wide frequency range, it is still a challenge to achieve high-precision and high-reconstruction-capability wideband spectrum sensing (WSS) under a very low SNR. We propose a Time-...Show More
CBAM-SLAM: A Semantic SLAM Based on Attention Module in Dynamic Environment
2022 6th Asian Conference on Artificial Intelligence Technology (ACAIT)
Year: 2022 | Conference Paper |
Cited by: Papers (5)
Traditional visual SLAM systems are stable in static environments, but have low accuracy and unstable in dynamic condition, which affects positioning accuracy and mapping effects. To solve this problem, CBAM-SLAM is proposed in this paper which is a semantic SLAM system based on attention module in dynamic environment. First, we integrate the CBAM (Convolutional Block Attention Module) into the fe...Show More
Intelligent Detection of Mango Disease Spores Based on Mask Scoring R-CNN
2021 5th Asian Conference on Artificial Intelligence Technology (ACAIT)
Year: 2021 | Conference Paper |
Cited by: Papers (8)
In the process of mango cultivation, there has been a major threat of mango diseases and insect pests. Mango diseases and insect pests are diverse, including mango anthracnose, mango black spot disease and Curvularia leaf spot disease, and anthrax spores, Alternaria alternata and Curvularia spp Source of infection. By detecting the presence of these three kinds of spores, the future disease situat...Show More
Intelligent Detection of Underwater Fish Speed Characteristics Based on Deep Learning
2021 5th Asian Conference on Artificial Intelligence Technology (ACAIT)
Year: 2021 | Conference Paper |
Cited by: Papers (2)
At present, the breeding area of Hainan province is 58,000 hectares, and the breeding industry is an important economic source of Hainan province. As an important breeding object in Hainan province, the daily activities and abnormal behaviors of the fish have a direct impact on the breeding yield and the breeding income. For mariculture fish, changes in behaviour are often reflected in the importa...Show More
Accurate Prediction Scheme of Water Quality in Smart Mariculture With Deep Bi-S-SRU Learning Network
Juntao Liu;Chuang Yu;Zhuhua Hu;Yaochi Zhao;Yong Bai;Mingshan Xie;Jian Luo
In the smart mariculture, the timely and accurate predictions of water quality can help farmers take countermeasures before the ecological environment deteriorates seriously. However, the openness of the mariculture environment makes the variation of water quality nonlinear, dynamic and complex. Traditional methods face challenges in prediction accuracy and generalization performance. To address t...Show More
Constrained-Focal-Loss Based Deep Learning for Segmentation of Spores
Yaochi Zhao;Fusheng Lin;Shiguang Liu;Zhuhua Hu;Hui Li;Yong Bai
The statistics of disease spores is significant for early strategy design of disease control in precision agriculture. To obtain the statistics information of spores in microscopic images, it is crucial to segment spores from images. In this paper, we research a deep learning based method to segment spores, taking anthrax spores as the research objects. We first built an anthrax spore dataset cons...Show More
Automatic and Accurate Prediction of Key Water Quality Parameters Based on SRU Deep Learning in Mariculture
Juntao Liu;Chuang Yu;Zhuhua Hu;Yaochi Zhao;Xin Xia;Zhigang Tu;Ruoqing Li
2018 IEEE International Conference on Advanced Manufacturing (ICAM)
Year: 2018 | Conference Paper |
Cited by: Papers (16)
In smart mariculture, an automatic and accurate prediction of key water quality parameters is a significant and challenge issue. This paper focuses on the prediction of pH and water temperature parameters in key water quality parameters. Firstly, the water quality parameters are preprocessed by improved method. Then, the Pearson correlation coefficient method is used to find the correlation betwee...Show More
Recognition of Pyralidae Insects with Unmanned Monitoring Robot Based on Histogram Reverse Mapping and Invariant Moment
Zhuhua Hu;Boyi Liu;Yaochi Zhao;Mengxing Huang;Yong Bai;Fusheng Lin
2018 IEEE International Conference on Advanced Manufacturing (ICAM)
Year: 2018 | Conference Paper |
Many species of Pyralidae insects are the important pests in agriculture production. However, the manual detection and identification of Pyralidae insects are labor intensive, inefficient, and subjective factors can influence recognition accuracy. To address these shortcomings, an unmanned monitoring robot car is designed. Firstly, the robot gets images by performing a fixed action and detect whet...Show More
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