Results 71 to 80 of about 6,629,786 (241)

Advances and Challenges in Deep Learning-Based Change Detection for Remote Sensing Images: A Review through Various Learning Paradigms

Remote Sensing
Change detection (CD) in remote sensing (RS) imagery is a pivotal method for detecting changes in the Earth’s surface, finding wide applications in urban planning, disaster management, and national security.
Lukang Wang, Min Zhang, Xu Gao, Wenzhong Shi   +3 more
doaj   +1 more source

Architecture‐Driven Functional Coupling in Vertically Aligned Nanocomposites

Advanced Functional Materials, EarlyView.
Vertically aligned nanocomposites define a growth‐engineered architecture in which vertical interfaces, strain fields, defect pathways, and phase connectivity are created simultaneously. This review shows how these architectural features couple ferroic, optical, ionic, electrochemical, and device responses, establishing design rules and open challenges
Md Shatil Islam‐Shanto, Javier Zamudio‐García, Abraham Sánchez‐Caballero, David Marrero‐López, Vincenzo Esposito   +4 more
wiley   +1 more source

WSPolyp-SAM: Weakly Supervised and Self-Guided Fine-Tuning of SAM for Colonoscopy Polyp Segmentation

Applied Sciences
Ensuring precise segmentation of colorectal polyps holds critical importance in the early diagnosis and treatment of colorectal cancer. Nevertheless, existing deep learning-based segmentation methods are fully supervised, requiring extensive, precise ...
Tingting Cai, Hongping Yan, Kun Ding, Yan Zhang, Yueyue Zhou   +4 more
doaj   +1 more source

Nitride MXenes Beyond Carbides: Bridging the Gap Between Computational Prediction and Experimental Realization

Advanced Functional Materials, EarlyView.
Nitride MXenes remain constrained by a persistent gap between computational prediction and experimental realization. This Review identifies the thermodynamic, kinetic, and chemical barriers limiting their synthesis, critically evaluates emerging fabrication routes, and proposes a multidimensional computational‐experimental framework to accelerate the ...
Naresh Varnakavi, Masoud Soroush
wiley   +1 more source

From Weakly Supervised Learning to Active Learning

, 2022
Applied mathematics and machine computations have raised a lot of hope since the recent success of supervised learning. Many practitioners in industries have been trying to switch from their old paradigms to machine learning.
Cabannes, Vivien
core  

Learning Multimodal Latent Attributes [PDF]

, 2014
—The rapid development of social media sharing has created a huge demand for automatic media classification and annotation techniques. Attribute learning has emerged as a promising paradigm for bridging the semantic gap and addressing data sparsity via ...
Yanwei Fu, Tao Xiang, Fu, Y, Timothy M. Hospedales, Shaogang Gong, Xiang, T, Hospedales, TM, Gong, S   +7 more
core   +1 more source

Deep learning models (Weakly Supervised Baseline Precision and Recall).

, 2023
Deep learning models (Weakly Supervised Baseline Precision and Recall).
Abdul Ghafoor (849371), Ali Shariq Imran (8100131), Rakhi Batra (16907773), Zenun Kastrati (8100125), Sarang Shaikh (16907770), Sher Muhammad Daudpota (10340933)   +5 more
core   +1 more source

Field-based estimation of cotton seedling agronomic traits: Using UAV-LiDAR and weakly supervised semantic segmentation

Industrial Crops and Products
Accurate estimation of the cotton seedling Leaf Area Index (LAI) is essential for yield prediction and precision crop management. Traditional manual methods are limited by low throughput, while two-dimensional remote sensing techniques often struggle ...
Zhendong Zhang, Sheng Wen, Lei Zhang, Jiehong Wu, Fagang Liu, Zhiyin Deng, Sipei Li   +6 more
doaj   +1 more source

Learning Neural Sequence-to-Sequence Models from Weak Feedback with Bipolar Ramp Loss

Transactions of the Association for Computational Linguistics, 2019
In many machine learning scenarios, supervision by gold labels is not available and conse quently neural models cannot be trained directly by maximum likelihood estimation.
Jehl, Laura, Lawrence, Carolin, Riezler, Stefan   +2 more
doaj   +1 more source

Drop‐on‐Demand Printed Negative Dielectric Anisotropy Liquid Crystal Droplets for Adaptive Complex Beam Manipulation and Assessment

Advanced Functional Materials, EarlyView.
Printed negative‐dielectric‐anisotropy liquid‐crystal droplets enable multidimensional full‐vectorial optical‐field sensing across polarization, phase, and wavelength, while also generating tunable skyrmionic‐like complex optical fields. ABSTRACT Adaptive manipulation of vectorial optical fields is important for optical metrology, imaging, and ...
Jinge Guo, Xuke Qiu, Runchen Zhang, Qihao Han, Liangyu Deng, Yishun Lu, Zimo Zhao, Mengmeng Li, Waqas Kamal, Junseok Ma, Yongge Ma, Steve J. Elston, Alfonso A. Castrejón‐Pita, Stephen M. Morris, Chao He   +14 more
wiley   +1 more source