CITRUS DISEASE CLASSIFICATION WITH TRANSFER LEARNING AND CNN BASED MODELS

CNN based music emotion classification

Music emotion recognition (MER) is usually regarded as a multi-label tagging task, and each segment of music can inspire specific emotion tags. Most researchers extract acoustic features from music and explore the relations between these features and their corresponding emotion tags. Considering the inconsistency of emotions inspired by the same music segment for human beings, seeking for the k...

Learning FRAME Models Using CNN Filters

The convolutional neural network (ConvNet or CNN) has proven to be very successful in many tasks such as those in computer vision. Recently there has been growing interest in visualizing the knowledge discriminatively learned by CNNs, by generating images based on CNN features. This paper is a contribution towards this theme of research on knowledge visualization via image generation. Specifica...

Transfer Learning for Colonic Polyp Classification Using Off-the-Shelf CNN Features

Personalizing EEG-Based Affective Models with Transfer Learning

Individual differences across subjects and nonstationary characteristic of electroencephalography (EEG) limit the generalization of affective braincomputer interfaces in real-world applications. On the other hand, it is very time consuming and expensive to acquire a large number of subjectspecific labeled data for learning subject-specific models. In this paper, we propose to build personalized...

Group-Based Active Learning of Classification Models

Learning of classification models from real-world data often requires additional human expert effort to annotate the data. However, this process can be rather costly and finding ways of reducing the human annotation effort is critical for this task. The objective of this paper is to develop and study new ways of providing human feedback for efficient learning of classification models by labelin...