Multimedia datasets for anomaly detection: a review

P Kumari, AK Bedi, M Saini - Multimedia Tools and Applications, 2024 - Springer
Multimedia anomaly datasets play a crucial role in automated surveillance. They have a
wide range of applications expanding from outlier objects/situation detection to the detection …

[HTML][HTML] Depression recognition using a proposed speech chain model fusing speech production and perception features

M Du, S Liu, T Wang, W Zhang, Y Ke, L Chen… - Journal of Affective …, 2023 - Elsevier
Background Increasing depression patients puts great pressure on clinical diagnosis. Audio-
based diagnosis is a helpful auxiliary tool for early mass screening. However, current …

Recent advances in agricultural disease image recognition technologies: A review

S Bondre, D Patil - Concurrency and Computation: Practice …, 2023 - Wiley Online Library
In the world of intelligent agriculture, agricultural disease picture detection plays a critical
role. Plant disease identification must be efficient if agricultural production is to be increased …

A novel automated depression detection technique using text transcript

U Yadav, AK Sharma - International Journal of Imaging …, 2023 - Wiley Online Library
Depression is one of the most common mental illnesses, impacting billions of people
worldwide. The lack of existing resources is impeding the country's economic prosperity. As …

Review of automated depression detection: Social posts, audio and video, open challenges and future direction

U Yadav, AK Sharma, D Patil - Concurrency and Computation …, 2023 - Wiley Online Library
Depression is the primary cause of illness and injury in the country, with over 280 million
people suffering from it as per the 2021 survey. Depression is one of the most common …

Improving Depression estimation from facial videos with face alignment, training optimization and scheduling

ML Cañellas, CÁ Casado, L Nguyen… - arXiv preprint arXiv …, 2022 - arxiv.org
Deep learning models have shown promising results in recognizing depressive states using
video-based facial expressions. While successful models typically leverage using 3D-CNNs …

A Novel Machine Learning and Deep Learning Driven Prediction for Pre-diabetic Patients

S Shahakar, P Chopde, N Purohit… - 2023 6th …, 2023 - ieeexplore.ieee.org
Of late there has been a considerable rise in pre-diabetic patients. Pre-diabetic patients
need to keep a watchful eye on their sugar intake to avoid blood sugar spikes. Fruit is an …

HiQuE: Hierarchical Question Embedding Network for Multimodal Depression Detection

J Jung, C Kang, J Yoon, S Kim, J Han - Proceedings of the 33rd ACM …, 2024 - dl.acm.org
The utilization of automated depression detection significantly enhances early intervention
for individuals experiencing depression. Despite numerous proposals on automated …

Depression recognition from facial videos: Preprocessing and scheduling choices hide the architectural contributions

M Lage Cañellas, C Álvarez Casado… - Electronics …, 2023 - Wiley Online Library
Deep learning models have been widely applied in video‐based depression detection. It is
observed that the diversity of preprocessing, data augmentation, and optimization …

Machine learning-based detection of emotion based on voice

K Kathane, RM Shete, LB Damahe… - AIP Conference …, 2024 - pubs.aip.org
Recognition of emotion from a person's voice conveys the state of a person. There is
different state of emotions. Happy, sad, angry and neutral are the primary emotions of a …