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2026, Vol: 16, Issue: 6
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Research Article


Mobile-based deep learning approach for the early diagnosis of canine skin and eye diseases using mobileNetV2

Ayesha Taranum, Chandana M. Rao, Farhana Kausar, Ambika Padinjareveedu Raghavan.


Abstract
Background:
Canine skin and eye diseases are common and can lead to serious health complications if not detected early. Limited access to veterinary care in remote areas further delays diagnosis and treatment.

Aim:
This study aims to develop a mobile-based deep learning approach for the early diagnosis of canine skin and eye diseases using the MobileNetV2 architecture.

Methods:
A dataset comprising images of nine canine disease classes was collected and pre-processed. Data augmentation techniques were applied to improve model generalization. A MobileNetV2-based model was trained and evaluated, and the trained model was integrated into a mobile application for real-time disease classification.

Results:
The proposed model achieved a training accuracy of 93.22% and a validation accuracy of 86.31%. Comparative analysis demonstrated that MobileNetV2 outperformed InceptionV3 and ResNet50 in terms of accuracy and efficiency for mobile deployment.

Conclusion:
The proposed system provides an efficient, accessible, and cost-effective solution for early diagnosis of canine skin and eye diseases, particularly in resource-limited settings.

Key words: Canine diseases; Deep learning; MobileNetV2; Skin and eye diagnosis; Veterinary AI.


 
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How to Cite this Article
Pubmed Style

Taranum A, Rao CM, Kausar F, Raghavan AP. Mobile-based deep learning approach for the early diagnosis of canine skin and eye diseases using mobileNetV2. Open Vet. J.. 2026; 16(5): 2781-2791. doi:10.5455/OVJ.2026.v16.i5.20

Web Style

Taranum A, Rao CM, Kausar F, Raghavan AP. Mobile-based deep learning approach for the early diagnosis of canine skin and eye diseases using mobileNetV2. https://www.openveterinaryjournal.com/?mno=300006 [Access: June 10, 2026]. doi:10.5455/OVJ.2026.v16.i5.20

AMA (American Medical Association) Style

Taranum A, Rao CM, Kausar F, Raghavan AP. Mobile-based deep learning approach for the early diagnosis of canine skin and eye diseases using mobileNetV2. Open Vet. J.. 2026; 16(5): 2781-2791. doi:10.5455/OVJ.2026.v16.i5.20


Vancouver/ICMJE Style

Taranum A, Rao CM, Kausar F, Raghavan AP. Mobile-based deep learning approach for the early diagnosis of canine skin and eye diseases using mobileNetV2. Open Vet. J.. (2026), [cited June 10, 2026]; 16(5): 2781-2791. doi:10.5455/OVJ.2026.v16.i5.20


Harvard Style

Taranum, A., Rao, . C. M., Kausar, . F. & Raghavan, . A. P. (2026) Mobile-based deep learning approach for the early diagnosis of canine skin and eye diseases using mobileNetV2. Open Vet. J., 16 (5), 2781-2791. doi:10.5455/OVJ.2026.v16.i5.20


Turabian Style

Taranum, Ayesha, Chandana M. Rao, Farhana Kausar, and Ambika Padinjareveedu Raghavan. 2026. Mobile-based deep learning approach for the early diagnosis of canine skin and eye diseases using mobileNetV2. Open Veterinary Journal, 16 (5), 2781-2791. doi:10.5455/OVJ.2026.v16.i5.20


Chicago Style

Taranum, Ayesha, Chandana M. Rao, Farhana Kausar, and Ambika Padinjareveedu Raghavan. "Mobile-based deep learning approach for the early diagnosis of canine skin and eye diseases using mobileNetV2." Open Veterinary Journal 16 (2026), 2781-2791. doi:10.5455/OVJ.2026.v16.i5.20


MLA (The Modern Language Association) Style

Taranum, Ayesha, Chandana M. Rao, Farhana Kausar, and Ambika Padinjareveedu Raghavan. "Mobile-based deep learning approach for the early diagnosis of canine skin and eye diseases using mobileNetV2." Open Veterinary Journal 16.5 (2026), 2781-2791. Print. doi:10.5455/OVJ.2026.v16.i5.20


APA (American Psychological Association) Style

Taranum, A., Rao, . C. M., Kausar, . F. & Raghavan, . A. P. (2026) Mobile-based deep learning approach for the early diagnosis of canine skin and eye diseases using mobileNetV2. Open Veterinary Journal, 16 (5), 2781-2791. doi:10.5455/OVJ.2026.v16.i5.20


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