Results 101 to 110 of about 211,846 (266)

3D Printing of Soft Robotic Systems: Advances in Fabrication Strategies and Future Trends

Advanced Robotics Research, EarlyView.
Collectively, this review systematically examines 3D‐printed soft robotics, encompassing material selections, function integration, and manufacturing methodologies. Meanwhile, fabrication strategies are analyzed in order of increasing complexity, highlighting persistent challenges with proposed solutions.
Changjiang Liu, Bin Cui, Xumin Huang, Xiaoyu (Rayne) Zheng, T. Thang Vo‐Doan, Ruirui Qiao   +5 more
wiley   +1 more source

Fast Bayesian Optimization of Machine Learning Hyperparameters on Large Datasets

, 2017
Bayesian optimization has become a successful tool for hyperparameter optimization of machine learning algorithms, such as support vector machines or deep neural networks.
Bartels, Simon, Falkner, Stefan, Hennig, Philipp, Hutter, Frank, Klein, Aaron   +4 more
core  

Improving the Robustness of Visual Teach‐and‐Repeat Navigation Using Drift Error Correction and Event‐Based Vision for Low‐Light Environments

Advanced Robotics Research, EarlyView.
Visual teach‐and‐repeat (VTR) navigation allows robots to learn and follow routes without building a full metric map. We show that navigation accuracy for VTR can be improved by integrating a topological map with error‐drift correction based on stereo vision.
Fuhai Ling, Ze Huang, Tony J. Prescott
wiley   +1 more source

Continual Learning for Multimodal Data Fusion of a Soft Gripper

Advanced Robotics Research, EarlyView.
Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley   +1 more source

Agri Watch: Precision Plant Health Monitoring using Deep Learning [PDF]

E3S Web of Conferences
The growth of deep learning technologies allows us to achieve higher accuracy in the classification of plant diseases, as well as in other domains. This research reveals the performance of several DL approaches, including custom convolutional neural ...
Krishna Ujjwal, Bharadwaj Sreepada, Kaswan Vinit, Kumar Anuraj, Kaur Gursimran, Rana Pooja   +5 more
doaj   +1 more source

ChicGrasp: Imitation‐Learning‐Based Customized Dual‐Jaw Gripper Control for Manipulation of Delicate, Irregular Bio‐Products

Advanced Robotics Research, EarlyView.
Automated poultry processing lines still rely on humans to lift slippery, easily bruised carcasses onto a shackle conveyor. Deformability, anatomical variance, and hygiene rules make conventional suction and scripted motions unreliable. We present ChicGrasp, an end‐to‐end hardware‐software co‐designed imitation learning framework, to offer a ...
Amirreza Davar, Zhengtong Xu, Siavash Mahmoudi, Pouya Sohrabipour, Chaitanya Pallerla, Yu She, Wan Shou, Philip Glen Crandall, Dongyi Wang   +8 more
wiley   +1 more source

Deep Learning Approach for Predicting Efficiency in Organic Photovoltaics from 2D Molecular Images of D/A Pairs

Advanced Theory and Simulations, EarlyView.
This study highlights the potential of deep learning, particularly Convolutional Neural Networks (CNNs), for predicting the photovoltaic performance of organic solar cells. By leveraging 2D images representing donor/acceptor molecular pairs, the model accurately estimates key performance indicators proving that this image‐based approach offers a fast ...
Khoukha Khoussa, Patrick Lévêque, Larbi Boubchir   +2 more
wiley   +1 more source

A Novel Approach to Detect Drones Using Deep Convolutional Neural Network Architecture

Sensors
Over the past decades, drones have become more attainable by the public due to their widespread availability at affordable prices. Nevertheless, this situation sparks serious concerns in both the cyber and physical security domains, as drones can be ...
Hrishi Rakshit, Pooneh Bagheri Zadeh
doaj   +1 more source

Dynamic Display of Changing Posterior in Bayesian Survival Analysis: The Software [PDF]

We consider the problem of estimating an unknown distribution function in the presence of censoring under the conditions that a parametric model is believed to hold approximately.
Balasubramanian Narasimhan, Hani J. Doss
core   +1 more source

Multi‐Site Transfer Classification of Major Depressive Disorder: An fMRI Study in 3335 Subjects

Advanced Science, EarlyView.
The study proposes graph convolution network with sparse pooling to learn the hierarchical features of brain graph for MDD classification. Experiment is done on multi‐site fMRI samples (3335 subjects, the largest functional dataset of MDD to date) and transfer learning is applied, achieving an average accuracy of 70.14%.
Jianpo Su, Jian Qin, Hui Shen, Ling‐Li Zeng, Baojuan Li, Jin Liu, Xuemei Song, Li Liu, Weidan Pu, Tongjian Bai, Huaning Wang, Hong Yin, Kai Wang, Lingjiang Li, Dewen Hu   +14 more
wiley   +1 more source