Results 151 to 160 of about 41,575 (296)

DNN representations

Extracted layer activations from several pre-trained deep neural network (DNN) models using the Net2Brain Python ...
Clemens Georg Bartnik, Iris I.A. Groen
core  

Advancing forward osmosis predictions: A deep learning‐based surrogate modeling approach

Journal of the Science of Food and Agriculture, EarlyView.
Abstract BACKGROUND This study presents a deep learning‐based surrogate model for the rapid and accurate prediction of forward osmosis (FO) performance under diverse operating conditions. To assess the applicability of data‐driven approaches, several machine learning models – decision tree, random forest, support vector machine, and deep neural network
Hyeon Woo Park, Woo‐Ju Kim
wiley   +1 more source

Enhancing Rock Strength Prediction and Features Selection by Coupling Well Log Data and Deep Learning Approaches in Reservoir Geomechanics

International Journal for Numerical and Analytical Methods in Geomechanics, EarlyView.
ABSTRACT Accurate rock strength parameters play a vital role in petroleum and mining operations for sustainable drilling activities, and wellbore stability analysis. This study investigates the applicability of deep learning techniques for assessing data‐driven models, and to conduct parametric sensitivity examination for feature attributes ranking to ...
Mohammad Islam Miah, Md. Shakil Rahaman, Travis Wiens   +2 more
wiley   +1 more source

Control System for the Navigation of the Agricultural Robots: A Review

Journal of Field Robotics, EarlyView.
ABSTRACT Control systems for the navigation of autonomous agricultural robots—particularly those operating in uneven terrain and in the presence of static or dynamic obstacles—have advanced considerably in recent years. As conventional machinery evolves toward increasingly automated systems, the design of reliable navigation controllers has become ...
Edna Carolina Moriones Polanía, Hugo Rafacho Fernandes, Daniel Albiero, Angel Pontin Garcia   +3 more
wiley   +1 more source

From Prediction to Prevention: An Explainable GeoAI Framework for Flood Susceptibility and Urban Exposure Assessment Using Machine and Deep Learning Models

Sustainable Development, EarlyView.
ABSTRACT Rapid urbanisation and intensifying rainfall have increased cities' vulnerability to flooding, posing major challenges to sustainable development. Although machine learning models have improved flood prediction accuracy, most remain limited by their black‐box nature and lack of actionable insights.
Abdulwaheed Tella, Izni Zahidi, Chow Ming Fai, Chukwuma Okolie, Quoc Bao Pham   +4 more
wiley   +1 more source

Network Latency Estimation for Telesurgery Using Deep Reinforcement Learning

SmartBot, EarlyView.
Overview of the proposed two‐stage deep reinforcement learning framework for network latency prediction in telesurgery. The pipeline includes data collection from simulated catheter navigation sessions (Philippines–Botswana), feature engineering, DQN‐based direction prediction (85.8% accuracy), direction‐to‐value transformation, and value forecasting ...
Bakang Kgopolo, Rodrigo S. Jamisola Jr., Molaletsa Namoshe   +2 more
wiley   +1 more source

Congestion Control for DNN training clusters

The modern DNN workloads generate network traffic having striking differences with the conventional data-center traffic. DNN training jobs generate periodic traffic pattern where all subsequent flows depend on the completion of the currently running flow.
Narang, Sanjoli
core  

Collaboration post‐acquisition: The role of acquirers' motives

Strategic Management Journal, EarlyView.
Abstract Research Summary What role do collaborations with a target's partners play in an acquisition, and how do these collaborations evolve post‐acquisition? Research suggests that these collaborations are an important reason to acquire but often diminish post‐acquisition. But if they tend to diminish, why are they a reason to acquire?
Henning Piezunka, Helge Klapper, Michael Vetter, Joachim Henkel   +3 more
wiley   +1 more source

Synthesis of Amorphous‐Crystalline Mixture Boron Nitride for Balanced Resistive Switching Operation

Small, EarlyView.
An amorphous–crystalline mixture BN (acm‐BN) is synthesized through low‐pressure chemical vapor deposition, achieving balanced resistive switching with low SET voltage and stable RESET. High‐resolution transmission electron microscopy reveals that BN films are fully amorphous at 930 °C, a mixed amorphous–crystalline phase is achieved at 990 °C.
Kyung Jin Ahn, Do Kyeong Yun, Mi Hyang Park, Hong Woon Yun, Minh Chien Nguyen, Van Tu Vu, Huamin Li, Pallavi Aggarwal, Woo Jong Yu   +8 more
wiley   +1 more source

Early-Exit DNN Inference on HMPSoCs

Using Heterogeneous Multi-Processor System-on-Chips (HMPSoCs) for Deep Neural Network (DNN) inference has become commonplace in edge devices. However, reducing the DNN inference latency on resource-constrained edge devices remains a first-class ...
Pathania, Anuj, Aghapour, Ehsan, Meratnia, Nirvana, Khalilian Gourtani, Saeed, Pimentel, Andy   +4 more
core   +1 more source