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Found 7 papers, 0 papers with code
Stop Oversampling for Class Imbalance Learning: A Critical Review
Given data and methods in hand, we argue that oversampling in its current forms and methodologies is unreliable for learning from class imbalanced data and should be avoided in real-world applications.
Fuzzy Win-Win: A Novel Approach to Quantify Win-Win Using Fuzzy Logic
The classic win-win has a key flaw in that it cannot offer the parties the right amounts of winning because each party believes they are winners.
Deep learning for identification and face, gender, expression recognition under constraints
The main objective of this work is to test the ability of deep learning based automated computer system to identify not only persons, but also to perform recognition of gender, age, and facial expressions such as eye smile.
Deep Face Image Retrieval: a Comparative Study with Dictionary Learning
The comparative results of the experiments conducted on three standard face image datasets show that the best performers for face image retrieval are Alexlayer7 with $K$-means and SSF, Alexlayer6 with $K$-SVD and SSF, and Alexlayer6 with $K$-means and SSF.
Detailed Investigation of Deep Features with Sparse Representation and Dimensionality Reduction in CBIR: A Comparative Study
Research on content-based image retrieval (CBIR) has been under development for decades, and numerous methods have been competing to extract the most discriminative features for improved representation of the image content.
Distance and Similarity Measures Effect on the Performance of K-Nearest Neighbor Classifier -- A Review
This review attempts to answer this question through evaluating the performance (measured by accuracy, precision and recall) of the KNN using a large number of distance measures, tested on a number of real-world datasets, with and without adding different levels of noise.
Victory Sign Biometric for Terrorists Identification
Simple measurements for the fingers, in addition to the Hu Moments for the areas of the fingers were used to extract the geometric features of the shown part of the hand shown after segmentation.
