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Found 8 papers, 6 papers with code
Machine vision for vial positioning detection toward the safe automation of material synthesis
Although robot-based automation in chemistry laboratories can accelerate the material development process, surveillance-free environments may lead to dangerous accidents primarily due to machine control errors.
3D-C2FT: Coarse-to-fine Transformer for Multi-view 3D Reconstruction
Recently, the transformer model has been successfully employed for the multi-view 3D reconstruction problem.
Predicting failure characteristics of structural materials via deep learning based on nondestructive void topology
The combined PH and DML processing of 3D X-CT data is our unique approach enabling reliable failure predictions at the time of material examination based on void topology progressions, and the method can be extended to various nondestructive failure tests for practical use.
Online Assessment Misconduct Detection using Internet Protocol and Behavioural Classification
The mechanism for detecting the practices of online cheating is presented in the form of an e-cheating intelligent agent, comprising of an internet protocol (IP) detector and a behavioural monitor.
E-cheating Prevention Measures: Detection of Cheating at Online Examinations Using Deep Learning Approach -- A Case Study
The intelligence agent monitors the behaviour of the students and has the ability to prevent and detect any malicious practices.
Periocular Embedding Learning with Consistent Knowledge Distillation from Face
Overall, CKD empowers the sole periocular network to produce robust discriminative embeddings for periocular recognition in the wild.
Identification of Crystal Symmetry from Noisy Diffraction Patterns by A Shape Analysis and Deep Learning
On the other hand, the DL-based identification of crystal symmetry suffers from a drastic drop in accuracy for problems involving classification into tens or hundreds of symmetry classes (e. g., up to 230 space groups), severely limiting its practical usage.
Periocular Recognition in the Wild with Orthogonal Combination of Local Binary Coded Pattern in Dual-stream Convolutional Neural Network
We also introduce and share a new dataset for periocular in the wild, namely Ethnic-ocular dataset for benchmarking.
