To what extent are the processes of human learning analogous to the more elementary learning processes studied in animal-conditioning experiments? This question, and the broader goal of integrating mathematical models of animal and human learning, was the focus of my collaborative research at Stanford with Gordon Bower in the mid-1980s as well as my doctoral dissertation, which he supervised (G...

• We focused on data scarcity issues related to convolutional neural networks (CNNs). Twelve modern pre-trained CNNs were compared. This approach is less complex, and can be easily adopted. contribute four passive acoustic datasets, corresponding 90 h. achieved up 82% F1 score as few 25 verified calls. Progress in deep learning, more specifically using (CNNs) for the creation of classification ...

We develop an end-to-end deep-neural-network-based algorithm for classifying animal behavior using accelerometry data on the embedded system of artificial intelligence things (AIoT) device installed in a wearable collar tag. The proposed jointly performs feature extraction and classification utilizing set infinite-impulse-response (IIR) finite-impulse-response (FIR) filters together with multil...

Automatic detection and classification of animal sounds has many applications in biodiversity monitoring behavior. In the past twenty years, volume digitised wildlife sound available massively increased, automatic through deep learning now shows strong results. However, bioacoustics is not a single task but vast range small-scale tasks (such as individual ID, call type, emotional indication) wi...

background: alzheimer’s disease was known as a progressive neurodegenerative disorder in the elderly and is characterized by dementia and severe neuronal loss in the some regions of brain such as nucleus basalis magnocellularis. it plays an important role in the brain functions such as learning and memory. loss of cholinergic neurons of nucleus basalis magnocellularis by ibotenic acid can commo...