Results 61 to 70 of about 142,624 (305)

Remote Sensing Image Retrieval by Deep Attention Hashing With Distance-Adaptive Ranking

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023
With the joint advancement of numerous related fields of remote sensing, the amount of remote sensing data is growing exponentially. As an essential remote sensing Big Data management technique, content-based remote sensing image retrieval has attracted ...
Yichao Zhang, Xiangtao Zheng, Xiaoqiang Lu   +2 more
doaj   +1 more source

Landscape of BRAF transcript variants in human cancer

Molecular Oncology, EarlyView.
We investigate the annotation of BRAF variants, focusing on protein‐coding BRAF‐220 (formerly BRAF‐reference) and BRAF‐204 (BRAF‐X1). The IsoWorm pipeline allows us to quantify these variants in human cancer, starting from RNA‐sequencing data. BRAF‐204 is more abundant than BRAF‐220 and impacts patient survival.
Maurizio S. Podda, Danilo Tatoni, Gianluca Mattei, Alberto Magi, Romina D'Aurizio, Laura Poliseno   +5 more
wiley   +1 more source

Do Neural Ranking Models Intensify Gender Bias?

, 2020
Concerns regarding the footprint of societal biases in information retrieval (IR) systems have been raised in several previous studies. In this work, we examine various recent IR models from the perspective of the degree of gender bias in their retrieval
Bolukbasi Tolga, Devlin Jacob, Kulshrestha Juhi, Nguyen Tri, Pang Liang, Sebastian   +5 more
core   +1 more source

Data‐driven discovery of gene expression markers distinguishing pediatric acute lymphoblastic leukemia subtypes

Molecular Oncology, EarlyView.
This study investigates gene expression differences between two major pediatric acute lymphoblastic leukemia (ALL) subtypes, B‐cell precursor ALL, and T‐cell ALL, using a data‐driven approach consisting of biostatistics and machine learning methods. Following analysis of a discovery dataset, we find a set of 14 expression markers differentiating the ...
Mona Nourbakhsh, Nikola Tom, Anna Schrøder Lassen, Helene Brasch Lind Petersen, Ulrik Kristoffer Stoltze, Karin Wadt, Kjeld Schmiegelow, Matteo Tiberti, Elena Papaleo   +8 more
wiley   +1 more source

Multi-Perspective Relevance Matching with Hierarchical ConvNets for Social Media Search

, 2019
Despite substantial interest in applications of neural networks to information retrieval, neural ranking models have only been applied to standard ad hoc retrieval tasks over web pages and newswire documents.
Lin, Jimmy, Rao, Jinfeng, Ture, Ferhan, Yang, Wei, Zhang, Yuhao   +4 more
core   +1 more source

Information retrieval of mass encrypted data over multimedia networking with N-level vector model-based relevancy ranking [PDF]

, 2016
With an explosive growth in the deployment of networked applications over the Internet, searching the encrypted information that the user needs becomes increasingly important. However, the information search precision is quite low when using Vector space
Liu, Ran, Peng, Jinghui, Tang, Shanyu, Zhang, Liping   +3 more
core   +1 more source

Feature Fusion-Based Re-Ranking for Home Textile Image Retrieval

Mathematics
In existing image retrieval algorithms, negative samples often appear at the forefront of retrieval results. To this end, in this paper, we propose a feature fusion-based re-ranking method for home textile image retrieval, which utilizes high-level ...
Ziyi Miao, Lan Yao, Feng Zeng, Yi Wang, Zhiguo Hong   +4 more
doaj   +1 more source

Systematic profiling of cancer‐fibroblast interactions reveals drug combinations in ovarian cancer

Molecular Oncology, EarlyView.
Fibroblasts, cells in the tumor environment, support ovarian cancer cell growth and alter morphology and drug response. We used fibroblast and cancer cell co‐culture models to test 528 drugs and discovered new drugs for combination treatment. We showed that adding Vorinostat or Birinapant to standard chemotherapy may improve drug response, suggesting ...
Greta Gudoityte, Osheen Sharma, Laura Leuenberger, Emelie Wallin, Josefin Fernebro, Päivi Östling, Rebecka Bergström, Johan Lindberg, Ulrika Joneborg, Olli Kallioniemi, Brinton Seashore‐Ludlow   +10 more
wiley   +1 more source

Particular object retrieval with integral max-pooling of CNN activations [PDF]

, 2016
Recently, image representation built upon Convolutional Neural Network (CNN) has been shown to provide effective descriptors for image search, outperforming pre-CNN features as short-vector representations.
Jégou, Hervé, Sicre, Ronan, Tolias, Giorgos   +2 more
core   +1 more source

Convergence of Learning Dynamics in Information Retrieval Games

, 2019
We consider a game-theoretic model of information retrieval with strategic authors. We examine two different utility schemes: authors who aim at maximizing exposure and authors who want to maximize active selection of their content (i.e.
Ben-Porat, Omer, Rosenberg, Itay, Tennenholtz, Moshe   +2 more
core   +1 more source