Results 71 to 80 of about 12,457,928 (304)
Semantically Adaptive Image-to-image Translation for Domain Adaptation of Semantic Segmentation
Proceedings of the British Machine Vision Conference 2020, 2020 Paper will appear on BMVC ...
Luigi Musto, Andrea Zinelli
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SEMANTIC SEGMENTATION OF AERIAL IMAGES WITH AN ENSEMBLE OF CNNS [PDF]
ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016 This paper describes a deep learning approach to semantic segmentation of very high resolution (aerial) images. Deep neural architectures hold the promise of end-to-end learning from raw images, making heuristic feature design obsolete. Over the last decade this idea has seen a revival, and in recent years deep convolutional neural networks (CNNs) have
D. Marmanis +5 more
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Semantic Image Segmentation in Duckietown
Vestnik NSU. Series: Information Technologies, 2021 The article is devoted to evaluation of the applicability of existing semantic segmentation algorithms for the “Duckietown” simulator. The article explores classical semantic segmentation algorithms as well as ones based on neural networks. We also examined machine learning frameworks, taking into account all the limitations of the “Duckietown ...
D. E. Shabalina +3 more
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Keyword-based Image Color Re-rendering with Semantic Segmentation [PDF]
, 2017 Keyword-based image color re-rendering is a convenient way to enhance the color of images. Most methods only focus on the color characteristics of the image while ignoring the semantic meaning of different regions.
Jin, Bin +7 more
core +3 more sources
Grounding Large Language Models for Robot Task Planning Using Closed‐Loop State Feedback
Advanced Robotics Research, EarlyView.BrainBody‐Large Language Model (LLM) introduces a hierarchical, feedback‐driven planning framework where two LLMs coordinate high‐level reasoning and low‐level control for robotic tasks. By grounding decisions in real‐time state feedback, it reduces hallucinations and improves task reliability.
Vineet Bhat +4 more
wiley +1 more source
Scalable Cascade Inference for Semantic Image Segmentation [PDF]
Procedings of the British Machine Vision Conference 2012, 2012 Semantic image segmentation is a problem of simultaneous segmentation and recognition of an input image into regions and their associated categorical labels, such as person, car or cow. A popular way to achieve this goal is to assign a label to every pixel in the input image and impose simple structural constraints on the output label space.
Sturgess, P +3 more
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MedSeq: Semantic Segmentation for Medical Image Sequences
, 2022 MedSeq: Semantic Segmentation for Medical Image ...
X Zhang (6084905) +7 more
core
Multilevel Embedding and Dropout for Improved 3D Object Detection in Autonomous Driving Systems
Advanced Robotics Research, EarlyView.A plug‐in framework for RoI‐based 3D object detectors exploits previously untapped multi‐level information within RoI features. Its novel multi‐level embedding and dropout strategy enables the detection head to generate predictions at different feature levels.
Xiaohu Lu, Hayder Radha
wiley +1 more source
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingSemantic segmentation is a basic task in the interpretation of remote sensing images. Mainstream deep-learning-based semantic segmentation algorithms typically process images with small sizes.
Shiyan Pang +4 more
doaj +1 more source
Complexity, 2021 With the emergence of deep learning, computer vision has witnessed extensive advancement and has seen immense applications in multiple domains. Specifically, image captioning has become an attractive focal direction for most machine learning experts ...
Ariyo Oluwasammi +7 more
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