Results 91 to 100 of about 4,969,023 (298)
Weakly Supervised Domain Adversarial Neural Network for Deforestation Detection in Tropical Forests
Domain adaptation has proven to be suitable for alleviating domain discrepancies, which hinder the generalization capacity of classifiers. Among a few alternatives, domain adaptation techniques that align features in a domain-agnostic space through ...
Pedro Juan Soto Vega +4 more
doaj +1 more source
ABSTRACT Background B‐cell lymphoblastic lymphoma (B‐LBL) represents a rare variety of non‐Hodgkin lymphoma, with limited research on its biology, progression, and management. Methods A retrospective analysis was performed on the clinical characteristics of 256 patients aged ≤18 years who received treatment under the China Net Childhood Lymphoma (CNCL)‐
Zhijuan Liu +20 more
wiley +1 more source
Unsupervised Domain Adaptation by Backpropagation [PDF]
Top-performing deep architectures are trained on massive amounts of labeled data. In the absence of labeled data for a certain task, domain adaptation often provides an attractive option given that labeled data of similar nature but from a different ...
Ganin, Yaroslav, Lempitsky, Victor
core
ABSTRACT Bone tumours present significant challenges for affected patients, as multimodal therapy often leads to prolonged physical limitations. This is particularly critical during childhood and adolescence, as it can negatively impact physiological development and psychosocial resilience.
Jennifer Queisser +5 more
wiley +1 more source
Unsupervised Domain Adaptation with Similarity Learning
The objective of unsupervised domain adaptation is to leverage features from a labeled source domain and learn a classifier for an unlabeled target domain, with a similar but different data distribution. Most deep learning approaches to domain adaptation
Pinheiro, Pedro O.
core +1 more source
ABSTRACT Background Chronic kidney disease is a growing public health problem worldwide, and the number of patients requiring renal replacement therapy is steadily increasing. Türkiye has experienced a similar rise in both the incidence and prevalence of renal replacement therapy over the past decades; however, national‐level projections of future ...
Arzu Akgül +2 more
wiley +1 more source
Cross-Domain Recommendation via Deep Domain Adaptation [PDF]
The behavior of users in certain services could be a clue that can be used to infer their preferences and may be used to make recommendations for other services they have never used. However, the cross-domain relationships between items and user consumption patterns are not simple, especially when there are few or no common users and items across ...
Kanagawa, Heishiro +4 more
openaire +2 more sources
Mapping the evolution of mitochondrial complex I through structural variation
Respiratory complex I (CI) is crucial for bioenergetic metabolism in many prokaryotes and eukaryotes. It is composed of a conserved set of core subunits and additional accessory subunits that vary depending on the organism. Here, we categorize CI subunits from available structures to map the evolution of CI across eukaryotes. Respiratory complex I (CI)
Dong‐Woo Shin +2 more
wiley +1 more source
Reciprocal control of viral infection and phosphoinositide dynamics
Phosphoinositides, although scarce, regulate key cellular processes, including membrane dynamics and signaling. Viruses exploit these lipids to support their entry, replication, assembly, and egress. The central role of phosphoinositides in infection highlights phosphoinositide metabolism as a promising antiviral target.
Marie Déborah Bancilhon, Bruno Mesmin
wiley +1 more source
DC-LoRA: Domain correlation low-rank adaptation for domain incremental learning
Continual learning, characterized by the sequential acquisition of multiple tasks, has emerged as a prominent challenge in deep learning. During the process of continual learning, deep neural networks experience a phenomenon known as catastrophic ...
Lin Li +4 more
doaj +1 more source

