A review on image segmentation techniques for future research study. Int. J. Eng. Trends Technol. 35, 504–505 (2016). Article Google Scholar Dong, G., Yan, Y., Shen, C. & Wang, H. Real-time high-performance semantic image segmentation of urban street scenes. IEEE Trans. Intell. ...
Semantic segmentation, vital for applications ranging from autonomous driving to robotics, faces significant challenges in domains where collecting large annotated datasets is difficult or prohibitively expensive. In such contexts, such as medicine and agriculture, the scarcity of training images hampers prog...
The recent progress in DL-based cloud semantic segmentation in Sentinel-2 can be attributed to the proliferation of public CD datasets such as SPARCS27, S2-Hollstein28, Biome 810, 38-cloud29, CESBIO30, 95-Cloud31, and CloudCatalogue32. Nonetheless, these datasets have some well-known shortcomi...
Semantic segmentation is an essential issue in the computer vision field, the difficulty of which lies in the accurate prediction of the pixel level and the edge division of similar objects. The encoder-encoder structure is widely used in many methods to
doi:10.5194/isprs-archives-XLIII-B2-2022-485-2022BORDEAUX (Aquitaine, France)DEEP learningPOINT cloudCONVOLUTIONAL neural networksARTIFICIAL intelligenceMACHINE learningThe use of deep machine learning methods for semantic classification of city mesh models is...
1 Alireza Fathi 1 Caroline Pantofaru 1 Leonidas Guibas 1,4 Andrea Tagliasacchi 1,3 Frank Dellaert 1,2 Thomas Funkhouser 1 1Google Research 2Georgia Tech 3Simon Fraser University 4Stanford University Panoptic Neural Field Color Input Images Depth Instance Se...
Paper tables with annotated results for KRADA: Known-region-aware Domain Alignment for Open-set Domain Adaptation in Semantic Segmentation
Recent advances in self-supervised contrastive learning yield good image-level representation, which favors classification tasks but usually neglects pixel-level detailed information, leading to unsatisfactory transfer performance to dense prediction tasks such as semantic segmentation. In this work, we propo...
We defined the latter as “event cuts” and cuts within events as “continuous cuts” based on standard event segmentation20,21. Our data shows that film cuts are associated with widespread neural responses across the whole brain (Fig. 2). Importantly, channels in the MTL and temporal lobe ...
A brain–computer interface that decodes continuous language from non-invasive recordings would have many scientific and practical applications. Currently, however, non-invasive language decoders can only identify stimuli from among a small set of words