MELR: Meta-learning via modeling episode-level relationships for few-shot learning
Most recent few-shot learning (FSL) approaches are based on episodic training whereby
each episode samples few training instances (shots) per class to imitate the test condition …
each episode samples few training instances (shots) per class to imitate the test condition …
Task-aware part mining network for few-shot learning
Abstract Few-Shot Learning (FSL) aims at classifying samples into new unseen classes with
only a handful of labeled samples available. However, most of the existing methods are …
only a handful of labeled samples available. However, most of the existing methods are …
Exemplars and counterexemplars explanations for image classifiers, targeting skin lesion labeling
Explainable AI consists in developing mechanisms allowing for an interaction between
decision systems and humans by making the decisions of the formers understandable. This …
decision systems and humans by making the decisions of the formers understandable. This …
Optimasi Prediksi Bencana Banjir menggunakan Algoritma SVM untuk penentuan Daerah Rawan Bencana Banjir
S Dwiasnati, Y Devianto - Prosiding SISFOTEK, 2021 - seminar.iaii.or.id
Flooding is one factor that can cause an economic slowdown in the affected area. Bandung
is known as the" City of Flowers" and" City of Fashion," since the term refers to the city's …
is known as the" City of Flowers" and" City of Fashion," since the term refers to the city's …
A novel luminance-based algorithm for classification of semi-dark images
Featured Application The fundamental research is relevant to several applications involving
dynamic conditions in terms of of incoming image's lightning and overall visibility of content …
dynamic conditions in terms of of incoming image's lightning and overall visibility of content …
Image anomaly detection by aggregating deep pyramidal representations
Anomaly detection consists in identifying, within a dataset, those samples that significantly
differ from the majority of the data, representing the normal class. It has many practical …
differ from the majority of the data, representing the normal class. It has many practical …
Predict high school students' final grades using basic machine learning
S Sugiyanto - Journal of Applied Data Sciences, 2021 - bright-journal.org
To improve the quality of students, teachers must be able to take precautionary measures to
deal with students who are lacking or have the potential to experience deficiency. Student …
deal with students who are lacking or have the potential to experience deficiency. Student …
Supervised anomaly detection with highly imbalanced datasets using capsule networks
Detecting anomalous patterns in data is a relevant task in many practical applications, such
as defective items detection in industrial inspection systems, cancer identification in medical …
as defective items detection in industrial inspection systems, cancer identification in medical …
Effects of class imbalance problem in convolutional neural network based image classification
A Banerjee, K Ghosh, A Sarkar… - Advances in Smart …, 2021 - Springer
Abstract Convolutional Neural Networks (CNNs) have revolutionized the image
classification tasks to a greater extent. Various research works reported the high accuracy of …
classification tasks to a greater extent. Various research works reported the high accuracy of …
Machine learning techniques for morphologic and clinical features extraction of cerebral aneurysm
SRS Vidhya, AR Arunachalam - 2021 10th IEEE International …, 2021 - ieeexplore.ieee.org
Aneurysms in Cerebral area represent one of the significant health intimidation where the
existing testing practice for analysis is the process that is difficult, wide & complicated, slow …
existing testing practice for analysis is the process that is difficult, wide & complicated, slow …