Results 291 to 300 of about 6,300,985 (321)

A Framework for Comparison and Interpretation of Machine Learning Classifiers to Predict Autism on the ABIDE Dataset. [PDF]

Hum Brain Mapp
Dong Y, Batalle D, Deprez M.
europepmc   +1 more source

Interpretable Multiscale Convolutional Neural Network for Classification and Feature Visualization of Weak Raman Spectra of Biomolecules at Cell Membranes. [PDF]

ACS Sens
Chin CL, Chang CE, Chao L.
europepmc   +1 more source

Underwater image enhancement via multiscale disentanglement strategy. [PDF]

Sci Rep
Yan J, Hu H, Wang Y, Nawaz MW, Ur Rehman Junejo N, Guo E, Feng H.   +6 more
europepmc   +1 more source

Motion feature extraction using magnocellular-inspired spiking neural networks for drone detection. [PDF]

Front Comput Neurosci
Zheng J, Wan Y, Yang X, Zhong H, Du M, Wang G.   +5 more
europepmc   +1 more source

Explainable artificial intelligence for neuroimaging-based dementia diagnosis and prognosis

Martin SA, Zhao A, Qu J, Imms P, Irimia A, Barkhof F, Cole JH, the Alzheimer’s Disease Neuroimaging Initiative.   +7 more
europepmc   +1 more source

Enhancing Brain Age Prediction and Neurodegeneration Detection with Contrastive Learning on Regional Biomechanical Properties

Träuble J, Hiscox L, Johnson C, Aviles-Rivero A, Schönlieb C, Schierle GK.   +5 more
europepmc   +1 more source

Some of the next articles are maybe not open access.

Related searches:

SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation

International Conference on Learning Representations, 2023
With evolving data regulations, machine unlearning (MU) has become an important tool for fostering trust and safety in today's AI models. However, existing MU methods focusing on data and/or weight perspectives often grapple with limitations in ...
Chongyu Fan, Jiancheng Liu, Yihua Zhang, Dennis Wei, Eric Wong, Sijia Liu   +5 more
semanticscholar   +1 more source

Multi-Graph Fusion and Learning for RGBT Image Saliency Detection

IEEE transactions on circuits and systems for video technology (Print), 2021
RGB and thermal infrared (RGBT) image saliency detection is a relatively new direction in the field of computer vision. Combining the advantages of RGB images and T images can significantly improve detection performance.
Liming Huang, Kechen Song, Jie Wang, Menghui Niu, Yunhui Yan   +4 more
semanticscholar   +1 more source

Multi-Exposure Decomposition-Fusion Model for High Dynamic Range Image Saliency Detection

IEEE transactions on circuits and systems for video technology (Print), 2020
High dynamic range (HDR) imaging techniques have witnessed a great improvement in the past few decades. However, saliency detection task on HDR content is still far from well explored.
Xu Wang, Zhenhao Sun, Qiudan Zhang, Yuming Fang, Lin Ma, Shiqi Wang, S. Kwong   +6 more
semanticscholar   +1 more source

Classification Saliency-Based Rule for Visible and Infrared Image Fusion

IEEE Transactions on Computational Imaging, 2021
Existing image fusion methods always use hand-crafted fusion rules due to the uninterpretability of deep feature maps, which restrict the performance of networks and result in distortion.
Han Xu, Hao Zhang, Jiayi Ma
semanticscholar   +1 more source