Results 21 to 30 of about 3,572,550 (313)

DeepCXray: Automatically Diagnosing Diseases on Chest X-Rays Using Deep Neural Networks

IEEE Access, 2018
The automatic detection of diseases in images acquired through chest X-rays can be useful in clinical diagnosis because of a shortage of experienced doctors.
Xiuyuan Xu, Quan Guo, Jixiang Guo, Zhang Yi   +3 more
doaj   +1 more source

LSH-GAN enables in-silico generation of cells for small sample high dimensional scRNA-seq data

Communications Biology, 2022
LSH-GAN is a locality-sensitive hashing based generative adversarial model that can produce realistic cell samples from small sample single-cell scRNA-seq data.
Snehalika Lall, Sumanta Ray, Sanghamitra Bandyopadhyay   +2 more
doaj   +1 more source

Fully Connected Hashing Neural Networks for Indexing Large-Scale Remote Sensing Images

Mathematics, 2022
With the emergence of big data, the efficiency of data querying and data storage has become a critical bottleneck in the remote sensing community. In this letter, we explore hash learning for the indexing of large-scale remote sensing images (RSIs) with ...
Na Liu, Haiming Mou, Jun Tang, Lihong Wan, Qingdu Li, Ye Yuan   +5 more
doaj   +1 more source

brain-machine-intelligence/Platforms: version_1127 (4 Unity scenes)

, 2020
<p>This release includes 4 Unity environments.</p ...
brain-machine-intelligence
core   +1 more source

CyberLimb: a novel robotic prosthesis concept with shared and intuitive control

Journal of NeuroEngineering and Rehabilitation, 2022
Background Existing assistive technologies attempt to mimic biological functions through advanced mechatronic designs. In some occasions, the information processing demands for such systems require substantial information bandwidth and convoluted control
Nicolas Seppich, Nicholas Tacca, Kuo-Yi Chao, Milan Akim, Diego Hidalgo-Carvajal, Edmundo Pozo Fortunić, Alexander Tödtheide, Johannes Kühn, Sami Haddadin   +8 more
doaj   +1 more source

Special Issue on Recent Advances in Machine Learning and Computational Intelligence

, 2023
Machine learning and computational intelligence are currently high-profile research areas attracting the attention of many researchers [...
Pengfei Jia, Yue Wu, Xinglong Zhang
core   +1 more source

Machine learning systems in the IoT: Trustworthiness trade-offs for edge intelligence

, 2020
Machine learning systems (MLSys) are emerging in the Internet of Things (IoT) to provision edge intelligence, which is paving our way towards the vision of ubiquitous intelligence. However, despite the maturity of machine learning systems and the IoT, we
Hutiri, Wiebke (author), Ding, Aaron Yi (author)   +1 more
core   +1 more source

Winning algorithms in BCI Controlled Robot Contest in World Robot Contest 2022: BCI Turing Test

Brain Science Advances, 2023
The Turing Test is a method of testing whether a machine has human intelligence. A novel brain–computer interface (BCI) Turing Test was proposed in the BCI Controlled Robot Contest in World Robot Contest 2022.
Hangjie Yi, Dongjun Liu, Xuanyu Jin, Hangkui Zhang, Wanzeng Kong   +4 more
doaj   +1 more source

brain-machine-intelligence/task_complexity_2018 1.0.0

, 2020
Simulation code for the computational model of arbitration and corresponding group effect fMRI ...
DongjaeKim-KAIST, Dongjae Kim, brain-machine-intelligence   +2 more
core   +1 more source

AULoRA: Anomaly Understanding With Low-Rank Adaptation for Zero-Shot Anomaly Detection

IEEE Access
Zero-Shot Anomaly Detection (ZSAD) aims to identify anomalies in unseen categories or scenarios. Recently, Vision-Language Models (VLMs), most notably CLIP, have been utilized to enhance anomaly detection performance.
Seunghyun Oh, Seongsu Lee, Seunghye Chae, Youngmin Ro   +3 more
doaj   +1 more source