What question did this study set out to answer?

The aim is to develop a system that accurately recognizes dog emotions from facial images using deep learning.

April 23, 20260 citationsOpen Access

Dog Emotion Recognition Using Deep Learning with an Expandable Image Dataset

SPSagar R PatilJain University JKJanaki KandasamyJain University

Key Points

The aim is to develop a system that accurately recognizes dog emotions from facial images using deep learning.
Implemented a deep learning model with MobileNetV2 and LSTM to analyze image features.
Introduced an expandable dataset structure for continuous enhancement of the model.
Deployed the system as a real-time web application.
Achieved 72.5% accuracy in recognizing emotions.
Outperformed previous methods, including CNN and CNN+RNN, in identifying Angry, Happy, and Sad emotions.
Demonstrated capability for further performance improvements through dataset expansion.

Abstract

This work presents a deep learning-based system for recognizing canine emotions using facial images. The proposed model integrates a MobileNetV2 backbone with an LSTM module to capture spatial dependencies in image features. An expandable dataset structure is introduced, allowing continuous improvement without code modification. The system achieves 72.5% test accuracy and is deployed as a real-time Streamlit web application. The approach demonstrates improved performance over CNN and CNN+RNN baselines for three emotion classes: Angry, Happy, and Sad.

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