Results 61 to 70 of about 1,369,914 (322)
, 2017 Feature extraction is a procedure aimed at selecting and transforming a data set in order to increase the performance of a pattern recognition or machine learning system. Nowadays, since the amount of data available and its dimension is growing exponentially, it is a fundamental procedure to avoid overfitting and the curse of dimensionality, while, in ...
Martinez-Murcia, Francisco Jesus +2 more
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A stepwise emergence of evolution in the RNA world
FEBS Letters, EarlyView.How did biological evolution emerge from chemical reactions? This perspective proposes a gradual scenario of self‐organization among RNA molecules, where catalytic feedback on random mixtures plays the central role. Short oligomers cross‐ligate, and self‐assembly enables heritable variations. An event of template‐externalization marks the transition to
Philippe Nghe
wiley +1 more source
Ilkom Jurnal Ilmiah, 2022 This study aims to build a system to identify the ripeness level of chayote that can be done easily and without damaging the quality of the chayote.
Siska Anraeni +2 more
doaj +1 more source
FEBS Letters, EarlyView.B cells sense external mechanical forces and convert them into biochemical signals through mechanotransduction. Understanding how malignant B cells respond to physical stimuli represents a groundbreaking area of research. This review examines the key mechano‐related molecules and pathways in B lymphocytes, highlights the most relevant techniques to ...
Marta Sampietro +2 more
wiley +1 more source
On a shape adaptive image ray transform
, 2013 A conventional approach to image analysis is to perform separately feature extraction at a low level (such as edge detection) and follow this with high level feature extraction to determine structure (e.g.
Ah Reum, Oh, Nixon, Mark S.
core +1 more source
An Introduction to Feature Extraction [PDF]
, 2008 This chapter introduces the reader to the various aspects of feature extraction covered in this book. Section 1 reviews definitions and notations and proposes a unified view of the feature extraction problem. Section 2 is an overview of the methods and results presented in the book, emphasizing novel contributions. Section 3 provides the reader with an
André Elisseeff, Isabelle Guyon
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Evolutionary interplay between viruses and R‐loops
FEBS Letters, EarlyView.Viruses interact with specialized nucleic acid structures called R‐loops to influence host transcription, epigenetic states, latency, and immune evasion. This Perspective examines the roles of R‐loops in viral replication, integration, and silencing, and how viruses co‐opt or avoid these structures.
Zsolt Karányi +4 more
wiley +1 more source
An effective dual encoder network with a feature attention large kernel for building extraction
Geocarto InternationalTransformer models boost building extraction accuracy by capturing global features from images. However, convolutional networks’ potential in local feature extraction remains underutilized in CNN + Transformer models, limiting performance.
Shaobo Qiu +3 more
doaj +1 more source
Lightweight transformer image feature extraction network [PDF]
PeerJ Computer ScienceIn recent years, the image feature extraction method based on Transformer has become a research hotspot. However, when using Transformer for image feature extraction, the model’s complexity increases quadratically with the number of tokens entered.
Wenfeng Zheng +4 more
doaj +2 more sources
Purification tags markedly affect self‐aggregation of CPEB3
FEBS Letters, EarlyView.Although recombinant proteins are used to study protein aggregation in vitro, uncleaved tags can interfere with accurate interpretation. Our findings demonstrate that His₆‐GFP and His₁₂ tags significantly affect liquid droplet and amyloid fibril formation in the intrinsically disordered region (IDR) of mouse cytoplasmic polyadenylation element‐binding ...
Harunobu Saito +6 more
wiley +1 more source