Results 31 to 40 of about 11,603,043 (210)

Multi-Level 3D CNN for Learning Multi-Scale Spatial Features [PDF]

, 2019
3D object recognition accuracy can be improved by learning the multi-scale spatial features from 3D spatial geometric representations of objects such as point clouds, 3D models, surfaces, and RGB-D data.
Adarsh Krishnamurthy, Ghadai, Sambit, Soumik Sarkar, Sambit Ghadai, Aditya Balu, Lee, Xian Yeow, Xian Yeow Lee, Krishnamurthy, Adarsh, Sarkar, Soumik, Balu, Aditya   +9 more
core   +1 more source

Multi-scale module.

, 2021
Multi-scale module.
Shijun Li (165293), Lin Chen (54305), Yu Sun (18463), Ji Li (207201), He Gong (169894), Lili Fu (171544), Ye Mu (9358116)   +6 more
core   +1 more source

Multi-scale model of food drying: Current status and challenges [PDF]

, 2016
For a long time, food engineers have been trying to describe the physical phenomena that occur during food processing especially drying. Physics-based theoretical modeling is an important tool for the food engineers to reduce the hurdles of ...
Khan, M.I.H., Rahman, M.M., Joardder, Mohammad U.H., Pham, Nghia Duc, Karim, M.A.   +4 more
core   +1 more source

Multi-Scale Modelling of Sintering

, 2008
Multi-scale modelling of ...
Ruo Yu Huang, R Huang (4235968), Jing Zhe Pan, Jingzhe Pan (7212152)   +3 more
core   +4 more sources

Multiplexing Multi-Scale Features Network for Salient Target Detection

Applied Sciences
This paper proposes a multiplexing multi-scale features network (MMF-Network) for salient target detection to tackle the issue of incomplete detection structures when identifying salient targets across different scales.
Xiaoxuan Liu, Yanfei Peng, Gang Wang, Jing Wang   +3 more
doaj   +1 more source

Adaptive Weighted Multi-Level Fusion of Multi-Scale Features: A New Approach to Pedestrian Detection

, 2021
Great achievements have been made in pedestrian detection through deep learning. For detectors based on deep learning, making better use of features has become the key to their detection effect.
Qin Yu, Yao Xu
core   +1 more source

MBMF: Constructing memory banks of multi‐scale features for anomaly detection

IET Computer Vision
In industrial manufacturing, how to accurately classify defective products and locate the location of defects has always been a concern. Previous studies mainly measured similarity based on extracting single‐scale features of samples. However, only using
Yanfeng Sun, Haitao Wang, Yongli Hu, Huajie Jiang, Baocai Yin   +4 more
doaj   +1 more source

A Salient Object Detection Method Based on Boundary Enhancement

Sensors, 2023
Visual saliency refers to the human’s ability to quickly focus on important parts of their visual field, which is a crucial aspect of image processing, particularly in fields like medical imaging and robotics.
Falin Wen, Qinghui Wang, Ruirui Zou, Ying Wang, Fenglin Liu, Yang Chen, Linghao Yu, Shaoyi Du, Chengzhi Yuan   +8 more
doaj   +1 more source

Comparison of the learning accuracies using all the multi-scale features or only global graph features, spectral features, local graph features or morphological features.

, 2012
Comparison of the learning accuracies using all the multi-scale features or only global graph features, spectral features, local graph features or morphological features.
Bülent Yener (93879), Shayoni Ray (179927), William P. Daley (179931), Melinda Larsen (179933), Cemal Cagatay Bilgin (179924), Banu Baydil (179929)   +5 more
core   +1 more source

CLASSIFICATION OF AIRBORNE LASER SCANNING DATA USING GEOMETRIC MULTI-SCALE FEATURES AND DIFFERENT NEIGHBOURHOOD TYPES [PDF]

, 2016
In this paper, we address the classification of airborne laser scanning data. We present a novel methodology relying on the use of complementary types of geometric features extracted from multiple local neighbourhoods of different scale and type.
B. Jutzi, M. Weinmann, Jutzi, B., R. Blomley, Weinmann, M., Blomley, R.   +5 more
core   +2 more sources