Deep Convolutional Neural Networks (DCNN) are currently the predominant technique
commonly used to learn visual features from images. However, the complex structure of …

Handwritten character recognition is a challenging task in the field of image processing and
pattern recognition. The success of character recognition systems depends heavily on the …

Deep learning (DL) has become a powerful tool in many image classification applications
but often requires large training sets to achieve high accuracy. For applications where the …

Case management developed from a generalist model to a person-centred model aligned
with the evidence-informed evolution of best practice people-centred integrated care. Case …

Recent progress in the fields of AI and cognitive sciences opens up new challenges and
problems that were previously inaccessible to study. One of such modern tasks is recovering …

In this paper we propose a simple unsupervised approach to learning higher order features.
This model is based on the recent success of lightweight approaches such as SOMNet and …

As one of the most intensively researched topics, image classification has attracted
significant attention in recent years. Numerous approaches have been proposed to derive …

요 약본 논문은 비지도 특징학습을 위한 새로운 에너지기반 은닉변수 모델 (EBLVM) 을
제안한다. EBLVM 의 결합확률밀도함수는 심층 신경망에 의해 변환된 연속적인 가시변수와 …

Understanding human actions is crucial for establishing an effective interaction between an
assistive system and humans in the real world. Humans are able to understand others' …

Robust solutions to image classification is a challenging task since approaches should be
able to successfully discriminate between the different classes, whilst being able to …