Results 81 to 90 of about 16,826 (269)

Deep Learning Using Tiny Domain-Specific Datasets with Sparse Labels [PDF]

, 2021
Machine learning is an ever-expanding field of research, and recently deep learning has been the architecture of choice. However, traditional deep learning methodologies require substantial amounts of data to train their networks.
Smith, Thomas J
core   +2 more sources

Autonomous Machine Learning‐Based Classification and Arrangement of Submillimeter Objects Using a Capillary Force Gripper

Advanced Intelligent Discovery, EarlyView.
This study presents an automated system integrating a capillary force gripper and machine learning‐based object detection for sorting and placing submillimeter objects. The system achieved stable and simultaneous manipulation of four object types, with an average task time of 86.0 seconds and a positioning error of 157 ± 84 µm, highlighting its ...
Satoshi Ando, Naoto Watanabe, Chihiro Sekine, Shogen Sekiguchi, Ohmi Fuchiwaki   +4 more
wiley   +1 more source

Tiny Machine Learning for Classifying Specialty Coffees

Anais do XLII Simpósio Brasileiro de Telecomunicações e Processamento de Sinais
The consumption of specialty coffee has increased around the world. Specialty coffee is free from impurities and defects. Specialty coffee is produced in smaller quantities, and its production process is hard and expensive. Traditional coffee beans have defects that affect the flavor of the coffee.
Isabela V De Carvalho Motta, Felipe Augusto Pereira de Figueiredo, Samuel B Mafra   +2 more
openaire   +1 more source

Taguchi–Bayesian Sampling: A Roadmap for Polymer Database Construction Toward Small Representative Machine Learning

Advanced Intelligent Discovery, EarlyView.
This article establishes a Taguchi–Bayesian sampling strategy to reconstruct polymer processing–property landscape at minimal sampling cost, generically building the roadmap for materials database construction from sampling their vast design space. This sampling strategy is featured by an alternating lesson between uniformity and representativeness ...
Han Liu, Liantang Li
wiley   +1 more source

Personal HealthCare of Things: A novel paradigm and futuristic approach

CAAI Transactions on Intelligence Technology, EarlyView., 2023
Abstract This study provides an investigative approach and offers a complete review of research on Internet of Medical Things (IoMT), describing the progress in general and highlighting the research issues, trends, and future aspects of IoMT. Exploring a research strategy for IoMT systems is vital as the need for IoT in healthcare grows. By aggregating
Surbhi Gupta, Mohammad Shabaz, Ankur Gupta, Abdullah Alqahtani, Shtwai Alsubai, Isaac Ofori   +5 more
wiley   +1 more source

Developing a TinyML Image Classifier in an Hour

IEEE Open Journal of the Industrial Electronics Society
Tiny machine learning technologies are bringing intelligence ever closer to the sensor, thus enabling the key benefits of edge computing (e.g., reduced latency, improved data security, higher energy efficiency, and lower bandwidth consumption, also ...
Riccardo Berta, Ali Dabbous, Luca Lazzaroni, Danilo Pietro Pau, Francesco Bellotti   +4 more
doaj   +1 more source

Autonomous AI‐Driven Design for Skin Product Formulations

Advanced Intelligent Discovery, EarlyView.
This review presents a comprehensive closed‐loop framework for autonomous skin product formulation design. By integrating artificial intelligence‐driven experiment selection with automated multi‐tiered assays, the approach shifts development from trial‐and‐error to intelligent optimisation.
Yu Zhang, Yongrui Xiao, Chunlin Chen, Dimitrios Tsaoulidis, Kai Yang, Tao Chen   +5 more
wiley   +1 more source

An efficient deep learning model for brain tumour detection with privacy preservation

CAAI Transactions on Intelligence Technology, EarlyView., 2023
Abstract Internet of medical things (IoMT) is becoming more prevalent in healthcare applications as a result of current AI advancements, helping to improve our quality of life and ensure a sustainable health system. IoMT systems with cutting‐edge scientific capabilities are capable of detecting, transmitting, learning and reasoning.
Mujeeb Ur Rehman, Arslan Shafique, Imdad Ullah Khan, Yazeed Yasin Ghadi, Jawad Ahmad, Mohammed S. Alshehri, Mimonah Al Qathrady, Majed Alhaisoni, Muhammad H. Zayyan   +8 more
wiley   +1 more source

From Data to Discovery: Machine Learning–Enabled Intelligent Characterization of Two‐Dimensional Materials

Advanced Intelligent Discovery, EarlyView.
Machine learning serves as a central engine for the intelligent characterization of two‐dimensional materials by integrating multimodal techniques, including optical microscopy, spectroscopy, electron microscopy, and scanning probe microscopy (SPM). This unified framework enables automated, high‐throughput, and quantitative extraction of structural ...
Zhi‐Long Cao, Jia‐Xu Yan
wiley   +1 more source

Resource-aware Tiny Machine Learning for Battery-less System [PDF]

Powerful machine learning algorithms have been increasingly designed to achieve better accuracy, which however require a great amount of data and computing power relying on centralized cloud services. This generates a series of problems such as high cost,
Islam, Sahidul
core   +1 more source