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- research-articleJuly 2024
A Satellite Band Selection Framework for Amazon Forest Deforestation Detection Task
GECCO '24: Proceedings of the Genetic and Evolutionary Computation ConferenceJuly 2024, Pages 1300–1308https://doi.org/10.1145/3638529.3654000The conservation of tropical forests is a topic of significant social and ecological relevance due to their crucial role in the global ecosystem. Unfortunately, deforestation and degradation impact millions of hectares annually, necessitating government ...
- research-articleJuly 2024JUST ACCEPTED
Multi-modal LiDAR Point Cloud Semantic Segmentation with Salience Refinement and Boundary Perception
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), Just Accepted https://doi.org/10.1145/3674979Point cloud segmentation is essential for scene understanding, which provides advanced information for many applications, such as autonomous driving, robots, and virtual reality. To improve the accuracy and robustness of point cloud segmentation, many ...
- research-articleJune 2024
CID-SIMS: Complex indoor dataset with semantic information and multi-sensor data from a ground wheeled robot viewpoint
- Yidi Zhang,
- Ning An,
- Chenhui Shi,
- Shuo Wang,
- Hao Wei,
- Pengju Zhang,
- Xinrui Meng,
- Zengpeng Sun,
- Jinke Wang,
- Wenliang Liang,
- Fulin Tang,
- Yihong Wu
International Journal of Robotics Research (RBRS), Volume 43, Issue 7Jun 2024, Pages 899–917https://doi.org/10.1177/02783649231222507Simultaneous localization and mapping (SLAM) and 3D reconstruction have numerous applications for indoor ground wheeled robots such as floor sweeping and food delivery. To advance research in leveraging semantic information and multi-sensor data to ...
- research-articleJune 2024
A Study on Semantic Segmentation for Small Objects in High-resolution Aerial Images based on Mask R-CNN and HRNet
ICMLC '24: Proceedings of the 2024 16th International Conference on Machine Learning and ComputingFebruary 2024, Pages 363–368https://doi.org/10.1145/3651671.3651695Due to the high resolution of aerial images, small objects in the images occupy very few pixels. Additionally, the surface features of some types of small objects are very similar, making them difficult to distinguish. These factors make semantic ...
- research-articleJune 2024
MiT: Land Parcel Segmentation Mask in Tokens
CVDL '24: Proceedings of the International Conference on Computer Vision and Deep LearningJanuary 2024, Article No.: 62, Pages 1–5https://doi.org/10.1145/3653804.3655995This study aims to address challenges such as data imbalance, diversity, and complexity in the task of semantic segmentation of remote sensing images. Inspired by PCT work, we designed a generative model based on VQVAE, transforming the pixel-level ...
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- research-articleMay 2024
Centroid Module for Shaping Feature Space in Semantic Segmentation
CACML '24: Proceedings of the 2024 3rd Asia Conference on Algorithms, Computing and Machine LearningMarch 2024, Pages 71–75https://doi.org/10.1145/3654823.3654837We propose Centroid Module (CM), a simple but effective module that improves the clustering ability of the image encoder in the semantic segmentation. Specifically, CM consists of a group of learnable parameters serving as the centroid of each category. ...
- extended-abstractMay 2024
Evaluation of Robustness of Off-Road Autonomous Driving Segmentation against Adversarial Attacks: A Dataset-Centric Study
AAMAS '24: Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent SystemsMay 2024, Pages 2237–2239The study explores the vulnerability of semantic segmentation models to adversarial input perturbations in the domain of off-road autonomous driving. Existing studies have primarily concentrated on enhancing model's robustness via architectural ...
- research-articleMay 2024
FIMD: Fusion-Inspired Modality Distillation for Enhanced MRI Segmentation in Incomplete Multi-Modal Scenarios
ICIGP '24: Proceedings of the 2024 7th International Conference on Image and Graphics ProcessingJanuary 2024, Pages 74–79https://doi.org/10.1145/3647649.3647661Magnetic Resonance Imaging (MRI) is an invaluable tool for brain tumor segmentation. However, in clinical practice, certain modalities might be unavailable, leading to potential performance degradation in prediction tasks. According to current ...
- ArticleApril 2024
MCNet: A Multi-scale and Cascade Network for Semantic Segmentation of Remote Sensing Images
AbstractHigh resolution remote sensing images that can show more detailed ground information play an important role in land classification. However, existing segmentation methods have the problems of insufficient use of multi-scale feature and semantic ...
- research-articleApril 2024
Machine and Deep Learning Implementations for Heritage Building Information Modelling: A Critical Review of Theoretical and Applied Research
Journal on Computing and Cultural Heritage (JOCCH), Volume 17, Issue 3Article No.: 36, Pages 1–22https://doi.org/10.1145/3649442Research domain and Problem: HBIM modelling from point cloud data has become a crucial research topic in the last decade since it is potentially considered as the central data model paving the way for the digital heritage practice beyond digitization. ...
- research-articleMarch 2024
Architectural Floorplan Recognition via Iterative Semantic Segmentation Networks
CSAI '23: Proceedings of the 2023 7th International Conference on Computer Science and Artificial IntelligenceDecember 2023, Pages 282–287https://doi.org/10.1145/3638584.3638636This paper presents a novel method for architectural floorplan recognition based on iterative semantic segmentation networks, effectively improving the segmentation performance of the network, achieving the semantic segmentation of floorplans, and ...
- research-articleMarch 2024
A modified UNet-based semantic segmentation architecture for pancreas tumour detection
International Journal of Bioinformatics Research and Applications (IJBRA), Volume 20, Issue 12024, Pages 1–20https://doi.org/10.1504/ijbra.2024.137372For computer aided diagnosis, computerised organ segmentation is a crucial but complicated task. The anatomy of the pancreas varies greatly and it is an abdominal organ. Especially when compared to other organs like the liver, heart, or kidneys, this ...
- ArticleMarch 2024
Characterization of Out-of-distribution Samples from Uncertainty Maps Using Supervised Machine Learning
AbstractThe quality of land use maps often refers to the data quality, but distributional uncertainty between training and test data must also be considered. In order to address this uncertainty, we follow the strategy to detect out-of-distribution ...
- research-articleMarch 2024
Human Selective Matting
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), Volume 20, Issue 6Article No.: 164, Pages 1–23https://doi.org/10.1145/3640017Existing human matting methods are incapable of accurately estimating the alpha mattes of arbitrarily selected humans from a group photo. An alternative solution is to apply them to the corresponding cropped image patches. However, this option obtains an ...
- ArticleMarch 2024
Genetic Algorithm Enhanced nnU-Net for the MICCAI KiTS23 Challenge
Kidney and Kidney Tumor SegmentationOct 2023, Pages 77–82https://doi.org/10.1007/978-3-031-54806-2_11AbstractDeep learning-based segmentation techniques have been gaining increasing attention in recent years due to their potential in various medical image segmentation tasks, particularly in the segmentation of kidneys, renal tumors, and renal cysts. One ...
- research-articleMarch 2024
Enhancing Few-Shot 3D Point Cloud Semantic Segmentation through Bidirectional Prototype Learning
ICRAI '23: Proceedings of the 2023 9th International Conference on Robotics and Artificial IntelligenceNovember 2023, Pages 7–16https://doi.org/10.1145/3637843.3637848In recent years, significant strides have been made in point cloud semantic segmentation, which, however, are unspectacular when the training is deprived of sufficient densely-annotated samples, especially with the face of new classes unseen during the ...
- research-articleMarch 2024
GF2DA: Gaussian Filter Fourier Domain Adaptation
FAIML '23: Proceedings of the 2023 International Conference on Frontiers of Artificial Intelligence and Machine LearningApril 2023, Pages 64–69https://doi.org/10.1145/3616901.3616916Deep learning has significantly advanced in computer vision, but the performance of these well-trained models often degrades in cross-domain situations due to domain differences. To solve this challenge, adversarial learning is widely utilized in domain ...
- research-articleMarch 2024
Problems with Deep Learning Application to Medical Data: Automatic Segmentation of Corneal Endothelium Layer
Procedia Computer Science (PROCS), Volume 225, Issue C2023, Pages 134–143https://doi.org/10.1016/j.procs.2023.09.100AbstractMachine learning is treated nowadays as a Holy Grall that solves all problems. However, it is difficult to deny a large area of application and high capabilities to deal with difficult problems, one should have in mind that there are still many ...
- research-articleFebruary 2024
SSS: Towards Autonomous Drone Delivery to Your Door Over House-Aware Semantics
HOTMOBILE '24: Proceedings of the 25th International Workshop on Mobile Computing Systems and ApplicationsFebruary 2024, Pages 33–39https://doi.org/10.1145/3638550.3641129In this work, we present our attempt to tackle the last-hundred-feet problem for autonomous drone delivery. We take a computer-vision-based approach to progressively landing towards a convenient and safe drop-off point at all times (here, at the front/...
- research-articleFebruary 2024
A Method for Breast Mass Segmentation using Image Augmentation with SAM and Receptive Field Expansion
ICCPR '23: Proceedings of the 2023 12th International Conference on Computing and Pattern RecognitionOctober 2023, Pages 387–394https://doi.org/10.1145/3633637.3633698With the development of deep learning methods and their wide application in medical image segmentation tasks, mammography, used for early breast cancer screening, can further assist clinicians in diagnosis to a certain extent. Due to the loss of fine-...