Results 101 to 110 of about 16,769 (297)

Weakly Supervised Object Localization with Multi-fold Multiple Instance Learning [PDF]

, 2015
International audienceObject category localization is a challenging problem in computer vision. Standard supervised training requires bounding box annotations of object instances. This time-consuming annotation process is sidestepped in weakly supervised
Cinbis, Ramazan Gokberk, Schmid, Cordelia, Verbeek, J., Schmid, C., Verbeek, Jakob, Ramazan Gokberk Cinbis, Cinbis, R. G., Jakob Verbeek, Cordelia Schmid   +8 more
core   +2 more sources

A weakly-supervised follicle segmentation method in ultrasound images

Scientific Reports
Accurate follicle segmentation in ultrasound images is crucial for monitoring follicle development, a key factor in fertility treatments. However, obtaining pixel-level annotations for fully supervised instance segmentation is often impractical due to ...
Guanyu Liu, Weihong Huang, Yanping Li, Qiong Zhang, Jing Fu, Hongying Tang, Jia Huang, Zhongteng Zhang, Lei Zhang, Yu Wang, Jianzhong Hu   +10 more
doaj   +1 more source

An Experimental High‐Throughput Approach for the Screening of Hard Magnet Materials

Advanced Engineering Materials, EarlyView.
An entire workflow for the high‐throughput characterization and analysis of compositionally graded magnetic films is presented. Characterization protocols, data management tools and data analysis approaches are illustrated with test case Sm(Fe, V)12 based films.
William Rigaut, Pierre Le Berre, Hamdi Jaballah, Lukas Fink, Victor Poline, Richard Haettel, Stéphane Grenier, Gilbert Chahine, Ewen Bellec, Guillaume Buatier, Wilfried Hortschitz, Santa Pile, Thomas Schrefl, Nils Blanc, Yuan Hong, Thibaut Devillers, Nora M. Dempsey   +16 more
wiley   +1 more source

Weakly supervised learning on pre-image problem in kernel methods [PDF]

, 2020
This paper presents a novel alternative approach, namely weakly supervised learning ...
Pong C Yuen, Jian-Huang Lai, Wei-Shi Zheng   +2 more
core  

Microstructure Reconstruction in Battery Electrodes Using Machine Learning Based on Low‐Voltage Focused Ion Beam–Scanning Electron Microscopy Tomography Images

Advanced Engineering Materials, EarlyView.
Low‐voltage FIB‐SEM tomography combined with a image preprocessing pipeline improves phase contrast and enables reliable machine‐learning segmentation of conductive networks in lithium‐ion battery electrodes. Structural descriptors are extracted from segmented images, done semimanually and automated, and compared.
Lisa Beran, Vincent Nebel, Dominik Perius, Kshitij Kumar, Yannis Heim, Laura Bies, Tobias Kraus   +6 more
wiley   +1 more source

Weakly Supervised Learning of Heterogeneous Concepts in Videos [PDF]

, 2016
Typical textual descriptions that accompany online videos are 'weak': i.e., they mention the main concepts in the video but not their corresponding spatio-temporal locations. The concepts in the description are typically heterogeneous (e.g., objects, persons, actions).
Sohil Shah, Kuldeep Kulkarni, Arijit Biswas, Ankit Gandhi, Om Deshmukh, Larry S. Davis   +5 more
openaire   +2 more sources

A Weakly Supervised Network for Coarse-to-Fine Change Detection in Hyperspectral Images

Remote Sensing
Hyperspectral image change detection (HSI-CD) provides substantial value in environmental monitoring, urban planning and other fields. In recent years, deep-learning based HSI-CD methods have made remarkable progress due to their powerful nonlinear ...
Yadong Zhao, Zhao Chen
doaj   +1 more source

Integrated Field‐Free SOT Domain‐Wall Synapses and MTJ Stochastic Neurons for Hardware Boltzmann Machines

Advanced Functional Materials, EarlyView.
Field‐free spin‐orbit torque domain‐wall synapses integrated with stochastic MTJ neurons enable compact hardware Boltzmann machines. Leveraging intrinsic stochasticity and multi‐level conductance, the system achieves efficient probabilistic learning with high accuracy, demonstrating a scalable spintronic platform for energy‐efficient edge AI.
Aijaz H. Lone, Meng Tang, Camelia Florica, Bin He, Jingkai Xu, Selma Amara, Georgian Melinte, Xixiang Zhang, Gianluca Setti   +8 more
wiley   +1 more source

Marginalized average attentional network for weakly-supervised learning [PDF]

, 2020
© 7th International Conference on Learning Representations, ICLR 2019. All Rights Reserved. In weakly-supervised temporal action localization, previous works have failed to locate dense and integral regions for each entire action due to the ...
Tsang IW, Yeung DY, Lyu Y, Shen X, Yuan Y   +4 more
core  

A General Formulation for Safely Exploiting Weakly Supervised Data [PDF]

, 2018
Weakly supervised data helps improve learning performance, which is an important machine learning data. However, recent results indicate that machine learning techniques with the usage of weakly supervised data may sometimes lead to performance ...
Guo, Lan-Zhe, Li, Yu-Feng
core   +1 more source