Results 111 to 120 of about 1,037,857 (302)
Feedbackward Decoding for Semantic Segmentation
CoRR, 2019 We propose a novel approach for semantic segmentation that uses an encoder in the reverse direction to decode. Many semantic segmentation networks adopt a feedforward encoder-decoder architecture. Typically, an input is first downsampled by the encoder to extract high-level semantic features and continues to be fed forward through the decoder module to
Beinan Wang +3 more
openaire +3 more sources
Exploiting Retentive Networks in 3D LiDAR Semantic Segmentation [PDF]
, 2023 openThe advent of LiDAR technology has revolutionized the fields of autonomous driving, robotics, and environmental monitoring by providing precise 3D point cloud data.
MOSCO, SIMONE
core
Comparison with supervised semantic segmentation methods.
, 2022 Comparison with supervised semantic segmentation methods.
Yunjing Xue (4416940) +5 more
core +1 more source
Learning Work Function via Implicit Reasoning on Electrostatic Potential Landscapes
Advanced Science, EarlyView.StructPot‐CLR establishes a cross‐modal contrastive learning framework that aligns the crystal structures of 2D materials with plane‐averaged electrostatic potential landscapes for physically informed work‐function prediction. The model achieves an MAE of 0.265 eV and an R2 of 0.902 on the held‐out test set while accurately preserving key morphological
Haoyu Wan, Yue Wu, Tianhao Su, Deng Pan
wiley +1 more source
Semantic Segmentation of Seismic Images
CoRR, 2019 Almost all work to understand Earth's subsurface on a large scale relies on the interpretation of seismic surveys by experts who segment the survey (usually a cube) into layers; a process that is very time demanding. In this paper, we present a new deep neural network architecture specially designed to semantically segment seismic images with a minimal
Daniel Civitarese +3 more
openaire +2 more sources
Semantic Segmentation Using Regions in Natural Scenes
, 2011 By introducing an over-segmentation algorithm into the conditional model (CM), we propose a new region-based CM model (R-CM), and investigate its performance on semantic segmentation of images. In order to incorporate structure information of objects, we
Hao YM(郝颖明) +2 more
core
Semantic segmentation diagram of lane lines.
, 2021 Semantic segmentation diagram of lane lines.
Lichao Chen (4782258) +4 more
core +1 more source
Advanced Science, EarlyView.MolDBG is a site‐aware, sequence‐only framework that unifies drug‐target affinity prediction, binding‐site identification, and affinity‐conditioned molecular generation for structured proteins. Guided by multi‐task binding‐site supervision, it aligns interaction‐critical residues before learning drug‐target representations and simultaneously infers ...
Gang Luo +6 more
wiley +1 more source
Artificial Intelligence‐Empowered Single‐Cell Phenotyping for Rapid, Automated Pathogen Diagnostics
Advanced Science, EarlyView.This work presents an integrated diagnostic platform that combines microfluidic single‐cell bacterial detection with artificial intelligence‐driven analysis for rapid antimicrobial susceptibility testing. Single‐cell phenotyping enables assessment of antibiotic response in only a few cell replication cycles, while AI analysis supports precise bacterial
Sabita Khadka +3 more
wiley +1 more source
Advanced Science, EarlyView.A novel targeted and pH‐responsive MRI contrast agent was integrated with a 3D nnU‐Net deep learning framework to enable accurate delineation of tumor boundary morphology in HER2‐positive breast cancer imaging. ABSTRACT Breast cancer continues to be a leading cause of cancer‐related mortality in women globally, where precise diagnosis and clear tumor ...
Jiaying Zheng +7 more
wiley +1 more source