Results 101 to 110 of about 11,006,319 (257)

Seismic Blind Deconvolution Based on Self-Supervised Machine Learning

Applied Sciences
Seismic deconvolution is a useful tool in seismic data processing. Classical non-machine learning deconvolution methods usually apply quite a few constraints to both wavelet inversion and reflectivity inversion.
Xia Yin, Wenhao Xu, Zhifang Yang, Bangyu Wu   +3 more
doaj   +1 more source

Blending With Insulating Polymers Enables Stable Anti‐Ambipolar Characteristics in n‐Type Organic Mixed‐Conductors for Heterogeneous Spiking Neurons

Advanced Materials, EarlyView.
A polymer blend of n‐type OMIEC P(gNDI‐gT2) with insulating PMMA yields mechanically stabilized, anti‐ambipolar organic electrochemical transistors (OECTs) with tunable ionic‐electronic transport. This blending allows low‐power, fast‐spiking heterogeneous Hodgkin–Huxley neurons, enabling biomimetic frequency deconvolution and reservoir computing, which
Zachary Laswick, Ariel Lifer, Catherine Beaumont, Liad Hayoun, Priscila Cavassin, Zeinab Hamid, Dilara Meli, William Dupont, Lincoln J. Lauhon, Iain McCulloch, Gitti L. Frey, Giovanni Maria Matrone, Jonathan Rivnay   +12 more
wiley   +1 more source

Ferroionic‐Assisted, Charge‐Driven Polymorphic Phase Engineering for Multilevel Memristive Devices

Advanced Materials, EarlyView.
A CuInP2S6/Mo0.92W0.08Te2 heterostructure enables a gradual semiconductor‐to‐semimetal phase transition through Cu+ ion migration and charge accumulation. The spatially engineered 2H/1T′ mixed phases produce continuously tunable conductance states in a two‐terminal geometry, while suppressing depolarizing fields and stabilizing the metastable 1T′ phase.
Nayeon Kim, Chengqi Wei, Eunji Hwang, Woohyun Cho, Heemyoung Hong, Yongjoon Lee, Daeho Noh, Min Seok Jang, Zhongrui Wang, Heejun Yang   +9 more
wiley   +1 more source

Optimized Self-Supervised Learning for MRI Reconstruction [PDF]

Supervised deep learning MRI reconstruction recovers images from accelerated MRI scans, but requires fully-sampled k-space for training. Self-supervised learning for MRI reconstruction bypasses the need for fully sampled k-space by partitioning under ...
Kadota, Brenden
core   +1 more source

Self‐supervised multi‐view clustering in computer vision: A survey

IET Computer Vision
In recent years, multi‐view clustering (MVC) has had significant implications in the fields of cross‐modal representation learning and data‐driven decision‐making.
Jiatai Wang, Zhiwei Xu, Xuewen Yang, Hailong Li, Bo Li, Xuying Meng   +5 more
doaj   +1 more source

Beyond Passivation: Designing Structurally Tailored Artificial Interphases for High‐Energy Lithium‐Based Anodes

Advanced Materials Interfaces, EarlyView.
This review outlines critical engineering design rules for building artificial protective coatings on next‐generation lithium metal and silicon battery anodes. It highlights how balancing structural flexibility with strict electronic and ionic transport limits prevents early battery failure.
Surin Gupte, Vilas G. Pol
wiley   +1 more source

Two‐Way Shape Memory Polymer Composite Gripper for Adaptive Robotic Applications

Advanced Materials Technologies, EarlyView.
A two‐way shape memory polymer (SMP) composite is developed with intrinsic shape‐changing capability driven solely by temperature, eliminating external actuation loads. Embedding the SMP in a low‐stiffness elastomeric matrix enabled reversible transformations during heating and cooling cycles.
Aamna Hameed, Kamran Ahmed Khan
wiley   +1 more source

Toward Perception‐Native Electronic Skin: Bio‐Inspired In‐/Near‐Sensor and Neuromorphic Computing for Humanoid Robots

Advanced Materials Technologies, EarlyView.
Dense tactile streams from across the humanoid body converge on collide in a central wiring and data bottleneck. By relocating computation closer to and then into the skin itself, near‐ and in‐sensor architectures, together with neuromorphic computing, chart a path toward perception‐native electronic skin, in which the conversion of stimulus into ...
Mijin Kim, Chang‐Jae Beak, Jiyoung Park, Youngdo Jung, Sunjong Oh, Sin‐Hyung Lee, Bo‐Yeon Lee   +6 more
wiley   +1 more source

Variational self-supervised learning

We present Variational Self-Supervised Learning (VSSL), a novel framework that combines variational inference with self-supervised learning to enable efficient, decoder-free representation learning.
Yavuz, Mehmet Can, Yanıkoğlu, Berrin
core   +1 more source

Self-supervised and supervised contrastive learning

, 2023
There has been a recent surge in the interest in contrastive learning due to its success in self-supervised learning for vision related tasks. The main goal of contrastive learning is to guide a model to learn an embedding space, where samples from the ...
Tan, Alvin De Jun
core