Results 21 to 30 of about 1,547,225 (303)

Intuitionistic Fuzzy c-Ordered Means Clustering Algorithm

IEEE Access, 2022
Atanassov intuitionistic fuzzy set (AIFS) has the capability to deal with various uncertain situations, so its popularity among researchers is quite high.
Meenakshi Kaushal, Q. M. Danish Lohani
doaj   +1 more source

The brain-inspired decoder for natural visual image reconstruction

Frontiers in Neuroscience, 2023
The visual system provides a valuable model for studying the working mechanisms of sensory processing and high-level consciousness. A significant challenge in this field is the reconstruction of images from decoded neural activity, which could not only ...
Wenyi Li, Wenyi Li, Shengjie Zheng, Shengjie Zheng, Yufan Liao, Rongqi Hong, Chenggang He, Chenggang He, Weiliang Chen, Weiliang Chen, Chunshan Deng, Xiaojian Li   +11 more
doaj   +1 more source

aryan-jadon/Regression-Loss-Functions-in-Time-Series-Forecasting-Tensorflow: Final Release

, 2023
This repository contains the implementation of paper Temporal Fusion Transformers for Interpretable Multi-horizon Time Series Forecasting with different loss functions in Tensorflow.
Aryan Jadon
core   +1 more source

Link Prediction of Weighted Triples for Knowledge Graph Completion Within the Scholarly Domain

IEEE Access, 2021
Knowledge graphs (KGs) are widely used for modeling scholarly communication, performing scientometric analyses, and supporting a variety of intelligent services to explore the literature and predict research dynamics.
Mojtaba Nayyeri, Gokce Muge Cil, Sahar Vahdati, Francesco Osborne, Andrey Kravchenko, Simone Angioni, Angelo Salatino, Diego Reforgiato Recupero, Enrico Motta, Jens Lehmann   +9 more
doaj   +1 more source

aryan-jadon/Regression-Loss-Functions-in-Time-Series-Forecasting-PyTorch: Final Release

, 2023
This repository compares the performance of 8 different regression loss functions used in Time Series Forecasting using Temporal Fusion ...
Aryan Jadon
core   +1 more source

A review of small object and movement detection based loss function and optimized technique

Journal of Intelligent Systems, 2023
The objective of this study is to supply an overview of research work based on video-based networks and tiny object identification. The identification of tiny items and video objects, as well as research on current technologies, are discussed first.
Chaturvedi Ravi Prakash, Ghose Udayan
doaj   +1 more source

Empirical Loss Landscape Analysis of Neural Network Activation Functions

, 2023
Activation functions play a significant role in neural network design by enabling non-linearity. The choice of activation function was previously shown to influence the properties of the resulting loss landscape.
Helbig, M, Helbig, Marde, Bosman, AS, Bosman, Anna Sergeevna, Engelbrecht, Andries, Engelbrecht, A   +5 more
core   +1 more source

davitshahnazaryan3/LOSS: LOSS

, 2021
Loss assessment framework for multi-storey buildings based on provided storey loss ...
Davit Shahnazaryan
core   +1 more source

U-Net-Based Models towards Optimal MR Brain Image Segmentation

Diagnostics, 2023
Brain tumor segmentation from MRIs has always been a challenging task for radiologists, therefore, an automatic and generalized system to address this task is needed.
Rammah Yousef, Shakir Khan, Gaurav Gupta, Tamanna Siddiqui, Bader M. Albahlal, Saad Abdullah Alajlan, Mohd Anul Haq   +6 more
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ACLASMA: Amplifying Cosine Losses for Anomalous Sound Monitoring in Automation

IEEE Access
Anomaly detection is an important application in factory environments. The sounds emitted by a manufacturing machine during runtime can be indicative of either normal performance or of mechanical failure.
Michael Goode Demoor, John Jeffery Prevost   +1 more
doaj   +1 more source