Results 101 to 110 of about 12,040,618 (293)

Object segmentation by fitting statistical shape models : a Kernel-based approach with application to wisdom tooth segmentation from CBCT images [PDF]

, 2014
Image segmentation is an important and challenging task in medical image analysis. Especially from low-quality images, segmentation algorithms have to cope with misleading background clutter, insufficient object boundaries and noise in the image ...
Jud, Christoph
core   +1 more source

Block-based Against Segmentation-based Texture Image Retrieval

, 2010
This paper concerns the best approach to the capture of local texture features for use in content-based image retrieval (CBIR) applications. From our previous work, two approaches have been suggested, the multiscale block-based approach and the automatic
Lewis, Paul, Fauzi, Mohammad Faizal Ahmad, Lewis,Paul, Fauzi,Mohammad Faizal Ahmad   +3 more
core   +2 more sources

A multilevel segmentation method of asymmetric semantics based on deep learning

IET Cyber-Physical Systems
An asymmetric semantic multi‐level segmentation method based on depth learning is proposed in order to improve the precision and effect of semantic segmentation.
Angxin Liu, Yongbiao Yang
doaj   +1 more source

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, Ali Umut Kaypak, Prashanth Krishnamurthy, Ramesh Karri, Farshad Khorrami   +4 more
wiley   +1 more source

Unsupervised colour image segmentation using dual-tree complex wavelet transform [PDF]

, 2010
In this paper we present an effective unsupervised colour image segmentation algorithm which uses multiscale edge information and spatial colour content. The multiscale edge information is extracted using the dual-tree complex wavelet transform.
Tjahjadi, Tardi, Çelik, Turgay
core   +1 more source

Explainable AI (XAI) in image segmentation in medicine, industry, and beyond: A survey

ICT Express
Explainable AI (XAI) has found numerous applications in computer vision. While image classification-based explainability techniques have garnered significant attention, their counterparts in semantic segmentation have been relatively neglected. Given the
Rokas Gipiškis, Chun-Wei Tsai, Olga Kurasova   +2 more
doaj   +1 more source

Semantic and Structural Image Segmentation for Prosthetic Vision

Jornada de Jóvenes Investigadores del I3A, 2019
We present a new approach to build a schematic representation of indoor environments for phosphene images. The proposed method combines a variety of convolutional neural networks for extracting and conveying relevant information about the scene such as structural informative edges of the environment and silhouettes of segmented objects.
Melani Sanchez-Garcia, Ruben Martinez-Cantin, Jose J. Guerrero   +2 more
openaire   +7 more sources

Multimodal Human–Robot Interaction Using Human Pose Estimation and Local Large Language Models

Advanced Robotics Research, EarlyView.
A multimodal human–robot interaction framework integrates human pose estimation (HPE) and a large language model (LLM) for gesture‐ and voice‐based robot control. Speech‐to‐text (STT) enables voice command interpretation, while a safety‐aware arbitration mechanism prioritizes gesture input for rapid intervention.
Nasiru Aboki, Ilche Georgievski, Marco Aiello   +2 more
wiley   +1 more source

Semantic segmentation of agricultural images: A survey

Information Processing in Agriculture
As an important research topic in recent years, semantic segmentation has been widely applied to image understanding problems in various fields. With the successful application of deep learning methods in machine vision, the superior performance has been
Zifei Luo, Wenzhu Yang, Yunfeng Yuan, Ruru Gou, Xiaonan Li   +4 more
doaj   +1 more source

DRIVE‐SAFE: Data‐Driven Robustness and Informed Validation for Evolving Specifications via Formal Evaluation

Advanced Robotics Research, EarlyView.
DRIVE‐SAFE evaluates learning‐based, black‐box autonomous driving policies against evolving temporal safety requirements using Signal Temporal Logic robustness metrics. It aggregates distributional robustness measures with domain‐informed weights to guide iterative retraining.
Kristy Sakano, Jianyu An, Dinesh Manocha, Huan Xu   +3 more
wiley   +1 more source